text:
an error on Mesos

Good afternoon.
Thank you for CaffeOnSpark. May I ask a question?
I tried to run the MNIST example on CaffeOnSpark. In the local mode it worked fine. But in the Mesos cluster mode, there was an error. Would you help me? I attached the Spark log below.
First, my command was:
/opt/spark-1.6.0-bin-hadoop2.6/bin/spark-submit \
    --files ${CAFFE_ON_SPARK}/data/lenet_memory_solver.prototxt.mesos,${CAFFE_ON_SPARK}/data/lenet_memory_train_test.prototxt.mesos \
    --conf spark.driver.extraLibraryPath="${LD_LIBRARY_PATH}" \
    --conf spark.executorEnv.LD_LIBRARY_PATH="${LD_LIBRARY_PATH}" \
    --class com.yahoo.ml.caffe.CaffeOnSpark  \
    ${CAFFE_ON_SPARK}/caffe-grid/target/caffe-grid-0.1-SNAPSHOT-jar-with-dependencies.jar \
        -train \
        -features accuracy,loss -label label \
        -conf ${CAFFE_ON_SPARK}/data/lenet_memory_solver.prototxt.mesos \
        -devices ${DEVICES} \
        -connection ethernet \
        -model hdfs:///mnist.model \
        -output hdfs:///mnist_features_result

I modified ${CAFFE_ON_SPARK}/data/lenet_memory_solver.prototxt.mesos so that it would look for ${CAFFE_ON_SPARK}/data/lenet_memory_train_test.prototxt.mesos in each worker computer. I copied lenet_memory_train_test.prototxt.mesos to each worker computer at the same path.
Then there was an error:
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/spark-1.6.0-bin-hadoop2.6/lib/spark-assembly-1.6.0-hadoop2.6.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/spark-1.6.0-bin-hadoop2.6/lib/spark-examples-1.6.0-hadoop2.6.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
16/06/16 15:46:49 INFO SparkContext: Running Spark version 1.6.0
16/06/16 15:46:49 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/06/16 15:46:49 INFO SecurityManager: Changing view acls to: hadoop
16/06/16 15:46:49 INFO SecurityManager: Changing modify acls to: hadoop
16/06/16 15:46:49 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(hadoop); users with modify permissions: Set(hadoop)
16/06/16 15:46:49 INFO Utils: Successfully started service 'sparkDriver' on port 33611.
16/06/16 15:46:49 INFO Slf4jLogger: Slf4jLogger started
16/06/16 15:46:49 INFO Remoting: Starting remoting
16/06/16 15:46:50 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriverActorSystem@192.168.0.2:53685]
16/06/16 15:46:50 INFO Utils: Successfully started service 'sparkDriverActorSystem' on port 53685.
16/06/16 15:46:50 INFO SparkEnv: Registering MapOutputTracker
16/06/16 15:46:50 INFO SparkEnv: Registering BlockManagerMaster
16/06/16 15:46:50 INFO DiskBlockManager: Created local directory at /tmp/blockmgr-7c2b7f3a-9a1a-4624-ace3-51bcdfa38d2e
16/06/16 15:46:50 INFO MemoryStore: MemoryStore started with capacity 511.1 MB
16/06/16 15:46:50 INFO SparkEnv: Registering OutputCommitCoordinator
16/06/16 15:46:50 INFO Utils: Successfully started service 'SparkUI' on port 4040.
16/06/16 15:46:50 INFO SparkUI: Started SparkUI at http://192.168.0.2:4040
16/06/16 15:46:50 INFO HttpFileServer: HTTP File server directory is /tmp/spark-e28ec4b7-cffb-474d-a920-e65632853235/httpd-a725ec82-a8f4-4e18-8577-b7dfcbb93a46
16/06/16 15:46:50 INFO HttpServer: Starting HTTP Server
16/06/16 15:46:50 INFO Utils: Successfully started service 'HTTP file server' on port 46356.
16/06/16 15:46:50 INFO SparkContext: Added JAR file:/home/hadoop/jaewoo.song/CaffeOnSpark/caffe-grid/target/caffe-grid-0.1-SNAPSHOT-jar-with-dependencies.jar at http://192.168.0.2:46356/jars/caffe-grid-0.1-SNAPSHOT-jar-with-dependencies.jar with timestamp 1466063210288
16/06/16 15:46:50 INFO Utils: Copying /home/hadoop/jaewoo.song/CaffeOnSpark/data/lenet_memory_solver.prototxt.mesos to /tmp/spark-e28ec4b7-cffb-474d-a920-e65632853235/userFiles-443ed678-92ee-404d-bf06-5fddafd23d08/lenet_memory_solver.prototxt.mesos
16/06/16 15:46:50 INFO SparkContext: Added file file:/home/hadoop/jaewoo.song/CaffeOnSpark/data/lenet_memory_solver.prototxt.mesos at http://192.168.0.2:46356/files/lenet_memory_solver.prototxt.mesos with timestamp 1466063210375
16/06/16 15:46:50 INFO Utils: Copying /home/hadoop/jaewoo.song/CaffeOnSpark/data/lenet_memory_train_test.prototxt.mesos to /tmp/spark-e28ec4b7-cffb-474d-a920-e65632853235/userFiles-443ed678-92ee-404d-bf06-5fddafd23d08/lenet_memory_train_test.prototxt.mesos
16/06/16 15:46:50 INFO SparkContext: Added file file:/home/hadoop/jaewoo.song/CaffeOnSpark/data/lenet_memory_train_test.prototxt.mesos at http://192.168.0.2:46356/files/lenet_memory_train_test.prototxt.mesos with timestamp 1466063210383
I0616 15:46:50.541450  3442 sched.cpp:222] Version: 0.28.0
2016-06-16 15:46:50,543:3351(0x7fc3593e4700):ZOO_INFO@log_env@712: Client environment:zookeeper.version=zookeeper C client 3.4.5
2016-06-16 15:46:50,543:3351(0x7fc3593e4700):ZOO_INFO@log_env@716: Client environment:host.name=hkcloud-node1
2016-06-16 15:46:50,543:3351(0x7fc3593e4700):ZOO_INFO@log_env@723: Client environment:os.name=Linux
2016-06-16 15:46:50,543:3351(0x7fc3593e4700):ZOO_INFO@log_env@724: Client environment:os.arch=3.10.0-327.10.1.el7.x86_64
2016-06-16 15:46:50,543:3351(0x7fc3593e4700):ZOO_INFO@log_env@725: Client environment:os.version=#1 SMP Tue Feb 16 17:03:50 UTC 2016
2016-06-16 15:46:50,543:3351(0x7fc3593e4700):ZOO_INFO@log_env@733: Client environment:user.name=hadoop
2016-06-16 15:46:50,544:3351(0x7fc3593e4700):ZOO_INFO@log_env@741: Client environment:user.home=/home/hadoop
2016-06-16 15:46:50,544:3351(0x7fc3593e4700):ZOO_INFO@log_env@753: Client environment:user.dir=/home/hadoop/jaewoo.song/CaffeOnSpark
2016-06-16 15:46:50,544:3351(0x7fc3593e4700):ZOO_INFO@zookeeper_init@786: Initiating client connection, host=hkcloud-m:2181,hkcloud-node1:2181,hkcloud-node2:2181 sessionTimeout=10000 watcher=0x7fc365896280 sessionId=0 sessionPasswd=<null> context=0x7fc398004680 flags=0
2016-06-16 15:46:50,547:3351(0x7fc3572df700):ZOO_INFO@check_events@1703: initiated connection to server [192.168.0.2:2181]
2016-06-16 15:46:50,556:3351(0x7fc3572df700):ZOO_INFO@check_events@1750: session establishment complete on server [192.168.0.2:2181], sessionId=0x25515b774600033, negotiated timeout=10000
I0616 15:46:50.556560  3437 group.cpp:349] Group process (group(1)@192.168.0.2:48907) connected to ZooKeeper
I0616 15:46:50.556592  3437 group.cpp:831] Syncing group operations: queue size (joins, cancels, datas) = (0, 0, 0)
I0616 15:46:50.556603  3437 group.cpp:427] Trying to create path '/mesos' in ZooKeeper
I0616 15:46:50.557202  3437 detector.cpp:152] Detected a new leader: (id='86')
I0616 15:46:50.557274  3437 group.cpp:700] Trying to get '/mesos/json.info_0000000086' in ZooKeeper
I0616 15:46:50.557571  3437 detector.cpp:479] A new leading master (UPID=master@192.168.0.3:5050) is detected
I0616 15:46:50.557610  3437 sched.cpp:326] New master detected at master@192.168.0.3:5050
I0616 15:46:50.557930  3437 sched.cpp:336] No credentials provided. Attempting to register without authentication
I0616 15:46:50.564281  3437 sched.cpp:703] Framework registered with a179a27d-cd33-4e1d-a996-5afec0bc1c4b-0035
16/06/16 15:46:50 INFO CoarseMesosSchedulerBackend: Registered as framework ID a179a27d-cd33-4e1d-a996-5afec0bc1c4b-0035
16/06/16 15:46:50 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 35384.
16/06/16 15:46:50 INFO NettyBlockTransferService: Server created on 35384
16/06/16 15:46:50 INFO BlockManagerMaster: Trying to register BlockManager
16/06/16 15:46:50 INFO BlockManagerMasterEndpoint: Registering block manager 192.168.0.2:35384 with 511.1 MB RAM, BlockManagerId(driver, 192.168.0.2, 35384)
16/06/16 15:46:50 INFO BlockManagerMaster: Registered BlockManager
16/06/16 15:46:50 INFO CoarseMesosSchedulerBackend: Mesos task 0 is now TASK_RUNNING
16/06/16 15:46:50 INFO CoarseMesosSchedulerBackend: Mesos task 1 is now TASK_RUNNING
16/06/16 15:46:50 INFO CoarseMesosSchedulerBackend: Mesos task 2 is now TASK_RUNNING
16/06/16 15:46:52 INFO CoarseMesosSchedulerBackend: Registered executor NettyRpcEndpointRef(null) (hkcloud-node2:49157) with ID f73f53d0-4f46-4691-ad01-5fed545d76e5-S0
16/06/16 15:46:52 INFO CoarseMesosSchedulerBackend: Registered executor NettyRpcEndpointRef(null) (hkcloud-node1:60208) with ID 753a7274-173a-41bf-b800-0345adc29be0-S0
16/06/16 15:46:52 INFO BlockManagerMasterEndpoint: Registering block manager hkcloud-node2:52796 with 511.1 MB RAM, BlockManagerId(f73f53d0-4f46-4691-ad01-5fed545d76e5-S0, hkcloud-node2, 52796)
16/06/16 15:46:52 INFO BlockManagerMasterEndpoint: Registering block manager hkcloud-node1:55612 with 511.1 MB RAM, BlockManagerId(753a7274-173a-41bf-b800-0345adc29be0-S0, hkcloud-node1, 55612)
16/06/16 15:46:52 INFO CoarseMesosSchedulerBackend: Registered executor NettyRpcEndpointRef(null) (hkcloud-m:60051) with ID 114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3
16/06/16 15:46:52 INFO BlockManagerMasterEndpoint: Registering block manager hkcloud-m:41380 with 511.1 MB RAM, BlockManagerId(114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3, hkcloud-m, 41380)
16/06/16 15:47:20 INFO CoarseMesosSchedulerBackend: SchedulerBackend is ready for scheduling beginning after waiting maxRegisteredResourcesWaitingTime: 30000(ms)
16/06/16 15:47:21 INFO DataSource$: Source data layer:0
16/06/16 15:47:21 INFO LMDB: Batch size:1
16/06/16 15:47:21 INFO SparkContext: Starting job: collect at CaffeOnSpark.scala:127
16/06/16 15:47:21 INFO DAGScheduler: Got job 0 (collect at CaffeOnSpark.scala:127) with 1 output partitions
16/06/16 15:47:21 INFO DAGScheduler: Final stage: ResultStage 0 (collect at CaffeOnSpark.scala:127)
16/06/16 15:47:21 INFO DAGScheduler: Parents of final stage: List()
16/06/16 15:47:21 INFO DAGScheduler: Missing parents: List()
16/06/16 15:47:21 INFO DAGScheduler: Submitting ResultStage 0 (MapPartitionsRDD[3] at map at CaffeOnSpark.scala:116), which has no missing parents
16/06/16 15:47:21 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 3.3 KB, free 3.3 KB)
16/06/16 15:47:21 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 2.1 KB, free 5.3 KB)
16/06/16 15:47:21 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 192.168.0.2:35384 (size: 2.1 KB, free: 511.1 MB)
16/06/16 15:47:21 INFO SparkContext: Created broadcast 0 from broadcast at DAGScheduler.scala:1006
16/06/16 15:47:21 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 0 (MapPartitionsRDD[3] at map at CaffeOnSpark.scala:116)
16/06/16 15:47:21 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks
16/06/16 15:47:21 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, hkcloud-node1, partition 0,PROCESS_LOCAL, 2209 bytes)
16/06/16 15:47:22 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on hkcloud-node1:55612 (size: 2.1 KB, free: 511.1 MB)
16/06/16 15:47:23 ERROR TaskSchedulerImpl: Lost executor 753a7274-173a-41bf-b800-0345adc29be0-S0 on hkcloud-node1: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:23 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, hkcloud-node1): ExecutorLostFailure (executor 753a7274-173a-41bf-b800-0345adc29be0-S0 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:23 INFO DAGScheduler: Executor lost: 753a7274-173a-41bf-b800-0345adc29be0-S0 (epoch 0)
16/06/16 15:47:23 INFO BlockManagerMasterEndpoint: Trying to remove executor 753a7274-173a-41bf-b800-0345adc29be0-S0 from BlockManagerMaster.
16/06/16 15:47:23 INFO BlockManagerMasterEndpoint: Removing block manager BlockManagerId(753a7274-173a-41bf-b800-0345adc29be0-S0, hkcloud-node1, 55612)
16/06/16 15:47:23 INFO TaskSetManager: Starting task 0.1 in stage 0.0 (TID 1, hkcloud-node2, partition 0,PROCESS_LOCAL, 2209 bytes)
16/06/16 15:47:23 INFO BlockManagerMaster: Removed 753a7274-173a-41bf-b800-0345adc29be0-S0 successfully in removeExecutor
16/06/16 15:47:23 INFO CoarseMesosSchedulerBackend: Mesos task 2 is now TASK_FAILED
16/06/16 15:47:23 INFO CoarseMesosSchedulerBackend: Mesos task 3 is now TASK_RUNNING
16/06/16 15:47:24 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on hkcloud-node2:52796 (size: 2.1 KB, free: 511.1 MB)
16/06/16 15:47:24 ERROR TaskSchedulerImpl: Lost executor f73f53d0-4f46-4691-ad01-5fed545d76e5-S0 on hkcloud-node2: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:24 WARN TaskSetManager: Lost task 0.1 in stage 0.0 (TID 1, hkcloud-node2): ExecutorLostFailure (executor f73f53d0-4f46-4691-ad01-5fed545d76e5-S0 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:24 INFO DAGScheduler: Executor lost: f73f53d0-4f46-4691-ad01-5fed545d76e5-S0 (epoch 1)
16/06/16 15:47:24 INFO BlockManagerMasterEndpoint: Trying to remove executor f73f53d0-4f46-4691-ad01-5fed545d76e5-S0 from BlockManagerMaster.
16/06/16 15:47:24 INFO BlockManagerMasterEndpoint: Removing block manager BlockManagerId(f73f53d0-4f46-4691-ad01-5fed545d76e5-S0, hkcloud-node2, 52796)
16/06/16 15:47:24 INFO BlockManagerMaster: Removed f73f53d0-4f46-4691-ad01-5fed545d76e5-S0 successfully in removeExecutor
16/06/16 15:47:24 INFO TaskSetManager: Starting task 0.2 in stage 0.0 (TID 2, hkcloud-m, partition 0,PROCESS_LOCAL, 2209 bytes)
16/06/16 15:47:24 INFO CoarseMesosSchedulerBackend: Mesos task 0 is now TASK_FAILED
16/06/16 15:47:24 INFO CoarseMesosSchedulerBackend: Mesos task 4 is now TASK_RUNNING
16/06/16 15:47:25 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on hkcloud-m:41380 (size: 2.1 KB, free: 511.1 MB)
16/06/16 15:47:25 ERROR TaskSchedulerImpl: Lost executor 114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3 on hkcloud-m: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:25 WARN TaskSetManager: Lost task 0.2 in stage 0.0 (TID 2, hkcloud-m): ExecutorLostFailure (executor 114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:25 INFO DAGScheduler: Executor lost: 114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3 (epoch 2)
16/06/16 15:47:25 INFO BlockManagerMasterEndpoint: Trying to remove executor 114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3 from BlockManagerMaster.
16/06/16 15:47:25 INFO BlockManagerMasterEndpoint: Removing block manager BlockManagerId(114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3, hkcloud-m, 41380)
16/06/16 15:47:25 INFO BlockManagerMaster: Removed 114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3 successfully in removeExecutor
16/06/16 15:47:25 INFO CoarseMesosSchedulerBackend: Registered executor NettyRpcEndpointRef(null) (hkcloud-node1:60216) with ID 753a7274-173a-41bf-b800-0345adc29be0-S0
16/06/16 15:47:25 INFO DAGScheduler: Host added was in lost list earlier: hkcloud-node1
16/06/16 15:47:25 INFO TaskSetManager: Starting task 0.3 in stage 0.0 (TID 3, hkcloud-node1, partition 0,PROCESS_LOCAL, 2209 bytes)
16/06/16 15:47:25 INFO CoarseMesosSchedulerBackend: Mesos task 1 is now TASK_FAILED
16/06/16 15:47:25 INFO BlockManagerMasterEndpoint: Registering block manager hkcloud-node1:56506 with 511.1 MB RAM, BlockManagerId(753a7274-173a-41bf-b800-0345adc29be0-S0, hkcloud-node1, 56506)
16/06/16 15:47:25 INFO CoarseMesosSchedulerBackend: Mesos task 5 is now TASK_RUNNING
16/06/16 15:47:26 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on hkcloud-node1:56506 (size: 2.1 KB, free: 511.1 MB)
16/06/16 15:47:26 INFO CoarseMesosSchedulerBackend: Registered executor NettyRpcEndpointRef(null) (hkcloud-node2:49171) with ID f73f53d0-4f46-4691-ad01-5fed545d76e5-S0
16/06/16 15:47:26 INFO DAGScheduler: Host added was in lost list earlier: hkcloud-node2
16/06/16 15:47:26 INFO BlockManagerMasterEndpoint: Registering block manager hkcloud-node2:36823 with 511.1 MB RAM, BlockManagerId(f73f53d0-4f46-4691-ad01-5fed545d76e5-S0, hkcloud-node2, 36823)
16/06/16 15:47:26 ERROR TaskSchedulerImpl: Lost executor 753a7274-173a-41bf-b800-0345adc29be0-S0 on hkcloud-node1: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:26 WARN TaskSetManager: Lost task 0.3 in stage 0.0 (TID 3, hkcloud-node1): ExecutorLostFailure (executor 753a7274-173a-41bf-b800-0345adc29be0-S0 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:26 ERROR TaskSetManager: Task 0 in stage 0.0 failed 4 times; aborting job
16/06/16 15:47:26 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool
16/06/16 15:47:26 INFO TaskSchedulerImpl: Cancelling stage 0
16/06/16 15:47:26 INFO DAGScheduler: ResultStage 0 (collect at CaffeOnSpark.scala:127) failed in 4.689 s
16/06/16 15:47:26 INFO DAGScheduler: Executor lost: 753a7274-173a-41bf-b800-0345adc29be0-S0 (epoch 3)
16/06/16 15:47:26 INFO DAGScheduler: Job 0 failed: collect at CaffeOnSpark.scala:127, took 4.909061 s
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, hkcloud-node1): ExecutorLostFailure (executor 753a7274-173a-41bf-b800-0345adc29be0-S0 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
Driver stacktrace:
	at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
	at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
	at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
	at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
	at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
	at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
	at scala.Option.foreach(Option.scala:236)
	at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
	at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
	at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
	at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:927)
	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
	at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
	at org.apache.spark.rdd.RDD.collect(RDD.scala:926)
	at com.yahoo.ml.caffe.CaffeOnSpark.train(CaffeOnSpark.scala:127)
	at com.yahoo.ml.caffe.CaffeOnSpark$.main(CaffeOnSpark.scala:40)
	at com.yahoo.ml.caffe.CaffeOnSpark.main(CaffeOnSpark.scala)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:497)
	at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
	at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
	at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
	at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
	at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
16/06/16 15:47:26 INFO SparkContext: Invoking stop() from shutdown hook
16/06/16 15:47:26 INFO BlockManagerMasterEndpoint: Trying to remove executor 753a7274-173a-41bf-b800-0345adc29be0-S0 from BlockManagerMaster.
16/06/16 15:47:26 INFO BlockManagerMasterEndpoint: Removing block manager BlockManagerId(753a7274-173a-41bf-b800-0345adc29be0-S0, hkcloud-node1, 56506)
16/06/16 15:47:26 INFO BlockManagerMaster: Removed 753a7274-173a-41bf-b800-0345adc29be0-S0 successfully in removeExecutor
16/06/16 15:47:26 INFO SparkUI: Stopped Spark web UI at http://192.168.0.2:4040
16/06/16 15:47:26 INFO CoarseMesosSchedulerBackend: Mesos task 3 is now TASK_FAILED
16/06/16 15:47:26 INFO CoarseMesosSchedulerBackend: Blacklisting Mesos slave 753a7274-173a-41bf-b800-0345adc29be0-S0 due to too many failures; is Spark installed on it?
16/06/16 15:47:26 INFO CoarseMesosSchedulerBackend: Shutting down all executors
16/06/16 15:47:26 INFO CoarseMesosSchedulerBackend: Asking each executor to shut down
I0616 15:47:26.619835  3641 sched.cpp:1903] Asked to stop the driver
I0616 15:47:26.622957  3433 sched.cpp:1143] Stopping framework 'a179a27d-cd33-4e1d-a996-5afec0bc1c4b-0035'
16/06/16 15:47:26 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
16/06/16 15:47:26 INFO CoarseMesosSchedulerBackend: driver.run() returned with code DRIVER_STOPPED
16/06/16 15:47:26 INFO MemoryStore: MemoryStore cleared
16/06/16 15:47:26 INFO BlockManager: BlockManager stopped
16/06/16 15:47:26 INFO BlockManagerMaster: BlockManagerMaster stopped
16/06/16 15:47:26 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
16/06/16 15:47:26 INFO RemoteActorRefProvider$RemotingTerminator: Shutting down remote daemon.
16/06/16 15:47:26 INFO RemoteActorRefProvider$RemotingTerminator: Remote daemon shut down; proceeding with flushing remote transports.
16/06/16 15:47:26 INFO SparkContext: Successfully stopped SparkContext
16/06/16 15:47:26 INFO ShutdownHookManager: Shutdown hook called
16/06/16 15:47:26 INFO ShutdownHookManager: Deleting directory /tmp/spark-e28ec4b7-cffb-474d-a920-e65632853235/httpd-a725ec82-a8f4-4e18-8577-b7dfcbb93a46
16/06/16 15:47:26 INFO ShutdownHookManager: Deleting directory /tmp/spark-e28ec4b7-cffb-474d-a920-e65632853235

I had changed the batch size to 1 to avoid any not-enough-memory problem. Meanwhile, a default example Spark program in spark-directory/example/src/main/python/pi.py ran fine in the setting. Also, the CaffeOnSpark MNIST example ran okay in a local mode.
Thank you for your time and concern.
Regards,
Jaewoo

Jaewoo:
I am not familiar with Spark on Mesos.
Your log indicates that one executor failed.

16/06/16 15:47:23 WARN TaskSetManager: Lost task 0.0 in stage 0.0
(TID 0, hkcloud-node1): ExecutorLostFailure (executor
753a7274-173a-41bf-b800-0345adc29be0-S0 exited caused by one of the
running tasks) Reason: Remote RPC client disassociated. Likely due to
containers exceeding thresholds, or network issues. Check driver logs
for WARN messages.
Please check out your executor log.
How many executors do you use? What's the value for ${DEVICES}?
Andy
Andy
On Thu, Jun 16, 2016 at 1:25 AM, jsongcse notifications@github.com wrote:

Good afternoon.
Thank you for CaffeOnSpark. May I ask a question?
I tried to run the MNIST example on CaffeOnSpark. In the local mode it
worked fine. But in the Mesos cluster mode, there was an error. Would you
help me? I attached the Spark log below.
First, my command was:
/opt/spark-1.6.0-bin-hadoop2.6/bin/spark-submit
--files ${CAFFE_ON_SPARK}/data/lenet_memory_solver.prototxt.mesos,${CAFFE_ON_SPARK}/data/lenet_memory_train_test.prototxt.mesos
--conf spark.driver.extraLibraryPath="${LD_LIBRARY_PATH}"
--conf spark.executorEnv.LD_LIBRARY_PATH="${LD_LIBRARY_PATH}"
--class com.yahoo.ml.caffe.CaffeOnSpark
${CAFFE_ON_SPARK}/caffe-grid/target/caffe-grid-0.1-SNAPSHOT-jar-with-dependencies.jar
-train
-features accuracy,loss -label label
-conf ${CAFFE_ON_SPARK}/data/lenet_memory_solver.prototxt.mesos
-devices ${DEVICES}
-connection ethernet
-model hdfs:///mnist.model
-output hdfs:///mnist_features_result
I modified ${CAFFE_ON_SPARK}/data/lenet_memory_solver.prototxt.mesos so
that it would look for
${CAFFE_ON_SPARK}/data/lenet_memory_train_test.prototxt.mesos in each
worker computer. I copied lenet_memory_train_test.prototxt.mesos to each
worker computer at the same path.
Then there was an error:
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/spark-1.6.0-bin-hadoop2.6/lib/spark-assembly-1.6.0-hadoop2.6.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/spark-1.6.0-bin-hadoop2.6/lib/spark-examples-1.6.0-hadoop2.6.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
16/06/16 15:46:49 INFO SparkContext: Running Spark version 1.6.0
16/06/16 15:46:49 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/06/16 15:46:49 INFO SecurityManager: Changing view acls to: hadoop
16/06/16 15:46:49 INFO SecurityManager: Changing modify acls to: hadoop
16/06/16 15:46:49 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(hadoop); users with modify permissions: Set(hadoop)
16/06/16 15:46:49 INFO Utils: Successfully started service 'sparkDriver' on port 33611.
16/06/16 15:46:49 INFO Slf4jLogger: Slf4jLogger started
16/06/16 15:46:49 INFO Remoting: Starting remoting
16/06/16 15:46:50 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriverActorSystem@192.168.0.2:53685]
16/06/16 15:46:50 INFO Utils: Successfully started service 'sparkDriverActorSystem' on port 53685.
16/06/16 15:46:50 INFO SparkEnv: Registering MapOutputTracker
16/06/16 15:46:50 INFO SparkEnv: Registering BlockManagerMaster
16/06/16 15:46:50 INFO DiskBlockManager: Created local directory at /tmp/blockmgr-7c2b7f3a-9a1a-4624-ace3-51bcdfa38d2e
16/06/16 15:46:50 INFO MemoryStore: MemoryStore started with capacity 511.1 MB
16/06/16 15:46:50 INFO SparkEnv: Registering OutputCommitCoordinator
16/06/16 15:46:50 INFO Utils: Successfully started service 'SparkUI' on port 4040.
16/06/16 15:46:50 INFO SparkUI: Started SparkUI at http://192.168.0.2:4040
16/06/16 15:46:50 INFO HttpFileServer: HTTP File server directory is /tmp/spark-e28ec4b7-cffb-474d-a920-e65632853235/httpd-a725ec82-a8f4-4e18-8577-b7dfcbb93a46
16/06/16 15:46:50 INFO HttpServer: Starting HTTP Server
16/06/16 15:46:50 INFO Utils: Successfully started service 'HTTP file server' on port 46356.
16/06/16 15:46:50 INFO SparkContext: Added JAR file:/home/hadoop/jaewoo.song/CaffeOnSpark/caffe-grid/target/caffe-grid-0.1-SNAPSHOT-jar-with-dependencies.jar at http://192.168.0.2:46356/jars/caffe-grid-0.1-SNAPSHOT-jar-with-dependencies.jar with timestamp 1466063210288
16/06/16 15:46:50 INFO Utils: Copying /home/hadoop/jaewoo.song/CaffeOnSpark/data/lenet_memory_solver.prototxt.mesos to /tmp/spark-e28ec4b7-cffb-474d-a920-e65632853235/userFiles-443ed678-92ee-404d-bf06-5fddafd23d08/lenet_memory_solver.prototxt.mesos
16/06/16 15:46:50 INFO SparkContext: Added file file:/home/hadoop/jaewoo.song/CaffeOnSpark/data/lenet_memory_solver.prototxt.mesos at http://192.168.0.2:46356/files/lenet_memory_solver.prototxt.mesos with timestamp 1466063210375
16/06/16 15:46:50 INFO Utils: Copying /home/hadoop/jaewoo.song/CaffeOnSpark/data/lenet_memory_train_test.prototxt.mesos to /tmp/spark-e28ec4b7-cffb-474d-a920-e65632853235/userFiles-443ed678-92ee-404d-bf06-5fddafd23d08/lenet_memory_train_test.prototxt.mesos
16/06/16 15:46:50 INFO SparkContext: Added file file:/home/hadoop/jaewoo.song/CaffeOnSpark/data/lenet_memory_train_test.prototxt.mesos at http://192.168.0.2:46356/files/lenet_memory_train_test.prototxt.mesos with timestamp 1466063210383
I0616 15:46:50.541450  3442 sched.cpp:222] Version: 0.28.0
2016-06-16 15:46:50,543:3351(0x7fc3593e4700):ZOO_INFO@log_env@712: Client environment:zookeeper.version=zookeeper C client 3.4.5
2016-06-16 15:46:50,543:3351(0x7fc3593e4700):ZOO_INFO@log_env@716: Client environment:host.name=hkcloud-node1
2016-06-16 15:46:50,543:3351(0x7fc3593e4700):ZOO_INFO@log_env@723: Client environment:os.name=Linux
2016-06-16 15:46:50,543:3351(0x7fc3593e4700):ZOO_INFO@log_env@724: Client environment:os.arch=3.10.0-327.10.1.el7.x86_64
2016-06-16 15:46:50,543:3351(0x7fc3593e4700):ZOO_INFO@log_env@725: Client environment:os.version=#1 SMP Tue Feb 16 17:03:50 UTC 2016
2016-06-16 15:46:50,543:3351(0x7fc3593e4700):ZOO_INFO@log_env@733: Client environment:user.name=hadoop
2016-06-16 15:46:50,544:3351(0x7fc3593e4700):ZOO_INFO@log_env@741: Client environment:user.home=/home/hadoop
2016-06-16 15:46:50,544:3351(0x7fc3593e4700):ZOO_INFO@log_env@753: Client environment:user.dir=/home/hadoop/jaewoo.song/CaffeOnSpark
2016-06-16 15:46:50,544:3351(0x7fc3593e4700):ZOO_INFO@zookeeper_init@786: Initiating client connection, host=hkcloud-m:2181,hkcloud-node1:2181,hkcloud-node2:2181 sessionTimeout=10000 watcher=0x7fc365896280 sessionId=0 sessionPasswd= context=0x7fc398004680 flags=0
2016-06-16 15:46:50,547:3351(0x7fc3572df700):ZOO_INFO@check_events@1703: initiated connection to server [192.168.0.2:2181]
2016-06-16 15:46:50,556:3351(0x7fc3572df700):ZOO_INFO@check_events@1750: session establishment complete on server [192.168.0.2:2181], sessionId=0x25515b774600033, negotiated timeout=10000
I0616 15:46:50.556560  3437 group.cpp:349] Group process (group(1)@192.168.0.2:48907) connected to ZooKeeper
I0616 15:46:50.556592  3437 group.cpp:831] Syncing group operations: queue size (joins, cancels, datas) = (0, 0, 0)
I0616 15:46:50.556603  3437 group.cpp:427] Trying to create path '/mesos' in ZooKeeper
I0616 15:46:50.557202  3437 detector.cpp:152] Detected a new leader: (id='86')
I0616 15:46:50.557274  3437 group.cpp:700] Trying to get '/mesos/json.info_0000000086' in ZooKeeper
I0616 15:46:50.557571  3437 detector.cpp:479] A new leading master (UPID=master@192.168.0.3:5050) is detected
I0616 15:46:50.557610  3437 sched.cpp:326] New master detected at master@192.168.0.3:5050
I0616 15:46:50.557930  3437 sched.cpp:336] No credentials provided. Attempting to register without authentication
I0616 15:46:50.564281  3437 sched.cpp:703] Framework registered with a179a27d-cd33-4e1d-a996-5afec0bc1c4b-0035
16/06/16 15:46:50 INFO CoarseMesosSchedulerBackend: Registered as framework ID a179a27d-cd33-4e1d-a996-5afec0bc1c4b-0035
16/06/16 15:46:50 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 35384.
16/06/16 15:46:50 INFO NettyBlockTransferService: Server created on 35384
16/06/16 15:46:50 INFO BlockManagerMaster: Trying to register BlockManager
16/06/16 15:46:50 INFO BlockManagerMasterEndpoint: Registering block manager 192.168.0.2:35384 with 511.1 MB RAM, BlockManagerId(driver, 192.168.0.2, 35384)
16/06/16 15:46:50 INFO BlockManagerMaster: Registered BlockManager
16/06/16 15:46:50 INFO CoarseMesosSchedulerBackend: Mesos task 0 is now TASK_RUNNING
16/06/16 15:46:50 INFO CoarseMesosSchedulerBackend: Mesos task 1 is now TASK_RUNNING
16/06/16 15:46:50 INFO CoarseMesosSchedulerBackend: Mesos task 2 is now TASK_RUNNING
16/06/16 15:46:52 INFO CoarseMesosSchedulerBackend: Registered executor NettyRpcEndpointRef(null) (hkcloud-node2:49157) with ID f73f53d0-4f46-4691-ad01-5fed545d76e5-S0
16/06/16 15:46:52 INFO CoarseMesosSchedulerBackend: Registered executor NettyRpcEndpointRef(null) (hkcloud-node1:60208) with ID 753a7274-173a-41bf-b800-0345adc29be0-S0
16/06/16 15:46:52 INFO BlockManagerMasterEndpoint: Registering block manager hkcloud-node2:52796 with 511.1 MB RAM, BlockManagerId(f73f53d0-4f46-4691-ad01-5fed545d76e5-S0, hkcloud-node2, 52796)
16/06/16 15:46:52 INFO BlockManagerMasterEndpoint: Registering block manager hkcloud-node1:55612 with 511.1 MB RAM, BlockManagerId(753a7274-173a-41bf-b800-0345adc29be0-S0, hkcloud-node1, 55612)
16/06/16 15:46:52 INFO CoarseMesosSchedulerBackend: Registered executor NettyRpcEndpointRef(null) (hkcloud-m:60051) with ID 114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3
16/06/16 15:46:52 INFO BlockManagerMasterEndpoint: Registering block manager hkcloud-m:41380 with 511.1 MB RAM, BlockManagerId(114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3, hkcloud-m, 41380)
16/06/16 15:47:20 INFO CoarseMesosSchedulerBackend: SchedulerBackend is ready for scheduling beginning after waiting maxRegisteredResourcesWaitingTime: 30000(ms)
16/06/16 15:47:21 INFO DataSource$: Source data layer:0
16/06/16 15:47:21 INFO LMDB: Batch size:1
16/06/16 15:47:21 INFO SparkContext: Starting job: collect at CaffeOnSpark.scala:127
16/06/16 15:47:21 INFO DAGScheduler: Got job 0 (collect at CaffeOnSpark.scala:127) with 1 output partitions
16/06/16 15:47:21 INFO DAGScheduler: Final stage: ResultStage 0 (collect at CaffeOnSpark.scala:127)
16/06/16 15:47:21 INFO DAGScheduler: Parents of final stage: List()
16/06/16 15:47:21 INFO DAGScheduler: Missing parents: List()
16/06/16 15:47:21 INFO DAGScheduler: Submitting ResultStage 0 (MapPartitionsRDD[3] at map at CaffeOnSpark.scala:116), which has no missing parents
16/06/16 15:47:21 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 3.3 KB, free 3.3 KB)
16/06/16 15:47:21 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 2.1 KB, free 5.3 KB)
16/06/16 15:47:21 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 192.168.0.2:35384 (size: 2.1 KB, free: 511.1 MB)
16/06/16 15:47:21 INFO SparkContext: Created broadcast 0 from broadcast at DAGScheduler.scala:1006
16/06/16 15:47:21 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 0 (MapPartitionsRDD[3] at map at CaffeOnSpark.scala:116)
16/06/16 15:47:21 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks
16/06/16 15:47:21 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, hkcloud-node1, partition 0,PROCESS_LOCAL, 2209 bytes)
16/06/16 15:47:22 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on hkcloud-node1:55612 (size: 2.1 KB, free: 511.1 MB)
16/06/16 15:47:23 ERROR TaskSchedulerImpl: Lost executor 753a7274-173a-41bf-b800-0345adc29be0-S0 on hkcloud-node1: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:23 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, hkcloud-node1): ExecutorLostFailure (executor 753a7274-173a-41bf-b800-0345adc29be0-S0 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:23 INFO DAGScheduler: Executor lost: 753a7274-173a-41bf-b800-0345adc29be0-S0 (epoch 0)
16/06/16 15:47:23 INFO BlockManagerMasterEndpoint: Trying to remove executor 753a7274-173a-41bf-b800-0345adc29be0-S0 from BlockManagerMaster.
16/06/16 15:47:23 INFO BlockManagerMasterEndpoint: Removing block manager BlockManagerId(753a7274-173a-41bf-b800-0345adc29be0-S0, hkcloud-node1, 55612)
16/06/16 15:47:23 INFO TaskSetManager: Starting task 0.1 in stage 0.0 (TID 1, hkcloud-node2, partition 0,PROCESS_LOCAL, 2209 bytes)
16/06/16 15:47:23 INFO BlockManagerMaster: Removed 753a7274-173a-41bf-b800-0345adc29be0-S0 successfully in removeExecutor
16/06/16 15:47:23 INFO CoarseMesosSchedulerBackend: Mesos task 2 is now TASK_FAILED
16/06/16 15:47:23 INFO CoarseMesosSchedulerBackend: Mesos task 3 is now TASK_RUNNING
16/06/16 15:47:24 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on hkcloud-node2:52796 (size: 2.1 KB, free: 511.1 MB)
16/06/16 15:47:24 ERROR TaskSchedulerImpl: Lost executor f73f53d0-4f46-4691-ad01-5fed545d76e5-S0 on hkcloud-node2: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:24 WARN TaskSetManager: Lost task 0.1 in stage 0.0 (TID 1, hkcloud-node2): ExecutorLostFailure (executor f73f53d0-4f46-4691-ad01-5fed545d76e5-S0 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:24 INFO DAGScheduler: Executor lost: f73f53d0-4f46-4691-ad01-5fed545d76e5-S0 (epoch 1)
16/06/16 15:47:24 INFO BlockManagerMasterEndpoint: Trying to remove executor f73f53d0-4f46-4691-ad01-5fed545d76e5-S0 from BlockManagerMaster.
16/06/16 15:47:24 INFO BlockManagerMasterEndpoint: Removing block manager BlockManagerId(f73f53d0-4f46-4691-ad01-5fed545d76e5-S0, hkcloud-node2, 52796)
16/06/16 15:47:24 INFO BlockManagerMaster: Removed f73f53d0-4f46-4691-ad01-5fed545d76e5-S0 successfully in removeExecutor
16/06/16 15:47:24 INFO TaskSetManager: Starting task 0.2 in stage 0.0 (TID 2, hkcloud-m, partition 0,PROCESS_LOCAL, 2209 bytes)
16/06/16 15:47:24 INFO CoarseMesosSchedulerBackend: Mesos task 0 is now TASK_FAILED
16/06/16 15:47:24 INFO CoarseMesosSchedulerBackend: Mesos task 4 is now TASK_RUNNING
16/06/16 15:47:25 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on hkcloud-m:41380 (size: 2.1 KB, free: 511.1 MB)
16/06/16 15:47:25 ERROR TaskSchedulerImpl: Lost executor 114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3 on hkcloud-m: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:25 WARN TaskSetManager: Lost task 0.2 in stage 0.0 (TID 2, hkcloud-m): ExecutorLostFailure (executor 114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:25 INFO DAGScheduler: Executor lost: 114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3 (epoch 2)
16/06/16 15:47:25 INFO BlockManagerMasterEndpoint: Trying to remove executor 114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3 from BlockManagerMaster.
16/06/16 15:47:25 INFO BlockManagerMasterEndpoint: Removing block manager BlockManagerId(114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3, hkcloud-m, 41380)
16/06/16 15:47:25 INFO BlockManagerMaster: Removed 114d8677-dbe9-4b2a-bf79-dc4a34d2cede-S3 successfully in removeExecutor
16/06/16 15:47:25 INFO CoarseMesosSchedulerBackend: Registered executor NettyRpcEndpointRef(null) (hkcloud-node1:60216) with ID 753a7274-173a-41bf-b800-0345adc29be0-S0
16/06/16 15:47:25 INFO DAGScheduler: Host added was in lost list earlier: hkcloud-node1
16/06/16 15:47:25 INFO TaskSetManager: Starting task 0.3 in stage 0.0 (TID 3, hkcloud-node1, partition 0,PROCESS_LOCAL, 2209 bytes)
16/06/16 15:47:25 INFO CoarseMesosSchedulerBackend: Mesos task 1 is now TASK_FAILED
16/06/16 15:47:25 INFO BlockManagerMasterEndpoint: Registering block manager hkcloud-node1:56506 with 511.1 MB RAM, BlockManagerId(753a7274-173a-41bf-b800-0345adc29be0-S0, hkcloud-node1, 56506)
16/06/16 15:47:25 INFO CoarseMesosSchedulerBackend: Mesos task 5 is now TASK_RUNNING
16/06/16 15:47:26 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on hkcloud-node1:56506 (size: 2.1 KB, free: 511.1 MB)
16/06/16 15:47:26 INFO CoarseMesosSchedulerBackend: Registered executor NettyRpcEndpointRef(null) (hkcloud-node2:49171) with ID f73f53d0-4f46-4691-ad01-5fed545d76e5-S0
16/06/16 15:47:26 INFO DAGScheduler: Host added was in lost list earlier: hkcloud-node2
16/06/16 15:47:26 INFO BlockManagerMasterEndpoint: Registering block manager hkcloud-node2:36823 with 511.1 MB RAM, BlockManagerId(f73f53d0-4f46-4691-ad01-5fed545d76e5-S0, hkcloud-node2, 36823)
16/06/16 15:47:26 ERROR TaskSchedulerImpl: Lost executor 753a7274-173a-41bf-b800-0345adc29be0-S0 on hkcloud-node1: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:26 WARN TaskSetManager: Lost task 0.3 in stage 0.0 (TID 3, hkcloud-node1): ExecutorLostFailure (executor 753a7274-173a-41bf-b800-0345adc29be0-S0 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
16/06/16 15:47:26 ERROR TaskSetManager: Task 0 in stage 0.0 failed 4 times; aborting job
16/06/16 15:47:26 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool
16/06/16 15:47:26 INFO TaskSchedulerImpl: Cancelling stage 0
16/06/16 15:47:26 INFO DAGScheduler: ResultStage 0 (collect at CaffeOnSpark.scala:127) failed in 4.689 s
16/06/16 15:47:26 INFO DAGScheduler: Executor lost: 753a7274-173a-41bf-b800-0345adc29be0-S0 (epoch 3)
16/06/16 15:47:26 INFO DAGScheduler: Job 0 failed: collect at CaffeOnSpark.scala:127, took 4.909061 s
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, hkcloud-node1): ExecutorLostFailure (executor 753a7274-173a-41bf-b800-0345adc29be0-S0 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:927)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.collect(RDD.scala:926)
at com.yahoo.ml.caffe.CaffeOnSpark.train(CaffeOnSpark.scala:127)
at com.yahoo.ml.caffe.CaffeOnSpark$.main(CaffeOnSpark.scala:40)
at com.yahoo.ml.caffe.CaffeOnSpark.main(CaffeOnSpark.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
16/06/16 15:47:26 INFO SparkContext: Invoking stop() from shutdown hook
16/06/16 15:47:26 INFO BlockManagerMasterEndpoint: Trying to remove executor 753a7274-173a-41bf-b800-0345adc29be0-S0 from BlockManagerMaster.
16/06/16 15:47:26 INFO BlockManagerMasterEndpoint: Removing block manager BlockManagerId(753a7274-173a-41bf-b800-0345adc29be0-S0, hkcloud-node1, 56506)
16/06/16 15:47:26 INFO BlockManagerMaster: Removed 753a7274-173a-41bf-b800-0345adc29be0-S0 successfully in removeExecutor
16/06/16 15:47:26 INFO SparkUI: Stopped Spark web UI at http://192.168.0.2:4040
16/06/16 15:47:26 INFO CoarseMesosSchedulerBackend: Mesos task 3 is now TASK_FAILED
16/06/16 15:47:26 INFO CoarseMesosSchedulerBackend: Blacklisting Mesos slave 753a7274-173a-41bf-b800-0345adc29be0-S0 due to too many failures; is Spark installed on it?
16/06/16 15:47:26 INFO CoarseMesosSchedulerBackend: Shutting down all executors
16/06/16 15:47:26 INFO CoarseMesosSchedulerBackend: Asking each executor to shut down
I0616 15:47:26.619835  3641 sched.cpp:1903] Asked to stop the driver
I0616 15:47:26.622957  3433 sched.cpp:1143] Stopping framework 'a179a27d-cd33-4e1d-a996-5afec0bc1c4b-0035'
16/06/16 15:47:26 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
16/06/16 15:47:26 INFO CoarseMesosSchedulerBackend: driver.run() returned with code DRIVER_STOPPED
16/06/16 15:47:26 INFO MemoryStore: MemoryStore cleared
16/06/16 15:47:26 INFO BlockManager: BlockManager stopped
16/06/16 15:47:26 INFO BlockManagerMaster: BlockManagerMaster stopped
16/06/16 15:47:26 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
16/06/16 15:47:26 INFO RemoteActorRefProvider$RemotingTerminator: Shutting down remote daemon.
16/06/16 15:47:26 INFO RemoteActorRefProvider$RemotingTerminator: Remote daemon shut down; proceeding with flushing remote transports.
16/06/16 15:47:26 INFO SparkContext: Successfully stopped SparkContext
16/06/16 15:47:26 INFO ShutdownHookManager: Shutdown hook called
16/06/16 15:47:26 INFO ShutdownHookManager: Deleting directory /tmp/spark-e28ec4b7-cffb-474d-a920-e65632853235/httpd-a725ec82-a8f4-4e18-8577-b7dfcbb93a46
16/06/16 15:47:26 INFO ShutdownHookManager: Deleting directory /tmp/spark-e28ec4b7-cffb-474d-a920-e65632853235
I had changed the batch size to 1 to avoid any not-enough-memory problem.
Meanwhile, a default example Spark program in
spark-directory/example/src/main/python/pi.py ran fine in the setting.
Also, the CaffeOnSpark MNIST example ran okay in a local mode.
Thank you for your time and concern.
Regards,
Jaewoo
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Dear Andy,
Good afternoon. Thank you for your reply.
Below is what I found in the log directory of spark master node. It seems there is not much information. (I tried to find logs of spark worker nodes but I couldn't.)
{"Event":"SparkListenerLogStart","Spark Version":"1.6.0"}
{"Event":"SparkListenerBlockManagerAdded","Block Manager ID":{"Executor ID":"driver","Host":"10.70.22.37","Port":60428},"Maximum Memory":1307836416,"Timestamp":1466481232878}

Three computers are used for Apache Spark, and the cluster manager is Apache Mesos. I chose 2 for ${DEVICES}.
Thank you for your help.
Regards,
Jaewoo

It was a problem about -clusterSize and -devices options. Apache Mesos also needs -clusterSize as same as YARN. Thank you for your help and encourage.

@jsongcse Please close this if it works. Would be great if you could send the doc for mesos setup (like the way we have a doc for yarn setup: https://github.com/yahoo/CaffeOnSpark/wiki/GetStarted_yarn)

Thank you for your help.

authors: anfeng jsongcse mriduljain

repo: yahoo/CaffeOnSpark


text:
Whether to support  Kafka 1.0.0？

I want to update Kafka to the version 1.0.0.
Can Kafka-manager  support  Kafka 1.0.0？
Thank  you very much!

it is not mentioned in the wiki hence i doubt on this..

mark

most things works fine so far for me. The only issue is that I can't see consumer lags anymore. wonder if it my config issue though

We are using kafka manager with kafka 1.0.0 just fine, we did have to restart the kafka manager, it showed negative lag, other than that we had no issues. We even did some operations through kafka manager like partition reassignment after we grew one of our kafka clusters in size.

@csueiras I can't get offsets to show up in kafka manager. are you persisting offset in zookeeper or kafka brokers?

@evollu we use kafka for offsets

@csueiras looks like I have to enable Display Broker and Topic Size to see LogSize and Lag?
So you made the patch to kafka 1.0.0?

We actually don't have that enabled, we definitely are getting lag metrics (we actually ingest those metrics through Kafka Manager's REST API).
We run a pretty vanilla configuration, we have the kafka 1.0.0 cluster as a "10.1.0" cluster in the manager.

@csueiras perhaps I'm off topic and I opened another issue https://github.com/yahoo/kafka-manager/issues/459. Can you help we check the configs?

Same here. The only difference is that it shows in the beginning "0.11" brokers version but haven't got any issues in meantime after kafka upgrade to 1.0.0.

It is available as a pull request: https://github.com/yahoo/kafka-manager/pull/454
We wait @patelh that he can validate and merge it on master

source: gharchive/issue

authors: BDeus YiGene csueiras evollu iMajna laoshancun pengkeboy

repo: yahoo/kafka-manager

license_type: permissive

license_source: bigquery


text:
Add Cache-Control header to mendel-middleware

Add Cache-Control header to mendel-middleware

Flawless

:+1:

source: gharchive/pull-request

authors: irae tufandevrim

repo: yahoo/mendel

license: mit


text:
Search not working after modyfying source

When modifying source of dataTable, table search in frontend is not working and returning empty table. Until I'm not writing in search it shows records by filtering. If there is solution to this or I need to use other search tools? Or I'm doing it all wrong?
/**
 * Build the DataTable class.
 *
 * @param QueryBuilder $query Results from query() method.
 */
public function dataTable(QueryBuilder $query): EloquentDataTable
{
    $user = Auth::user();

    $dataTable = new EloquentDataTable($query);

    $dataTable->addColumn('action', 'order.dt.actions')
        ->addColumn('date', function (Order $order) {
            return $order->created_at->format('Y-m-d');
        })
        ->addColumn('car_plate', function (Order $order) {
            return $order->car->number_plate ?? '';
        })
        ->addColumn('id', function (Order $order) {
            return $order->internal_id;
        })
        ->rawColumns(['action']);

    return $dataTable;
}

/**
 * Get the query source of dataTable.
 */
public function query(Order $model): QueryBuilder
{
    $user = Auth::user();
    return $model->where('driver_id', $user->driver_id)
                 ->orWhere('customer_id', $user->customer_id);
}

System details

Operating System macOS
PHP Version 8.2.0
Laravel Version 11
Laravel-Datatables Version 11

addColumn disables search/sort by default since it is considered computed and not part of the DB. You can use filterColumn to handle the search instead.

repo: yajra/laravel-datatables


text:
E-Mail Versand von Choice Values mit " und , funktioniert nicht

Wenn ich Dinge wie , " oder ½ in ein choice packe, wird das im Frontend zwar ordentlichangezeigt, beim E-Mail Versand ist das Value aber leer.
$yform->setValueField('choice', ['repairFlat','{{formClaim.repairFlat}}','{"44,50":"44,50","55,55":"55,55"}','0','0','','','','{{choose}}','','','','','1']);

Siehe -> #865

Das hat nichts mit dem E-Mail-Versand zu tun, sondern es geht rein um das Sanitizing der Eingabe. Ich schlage vor, hier zu schließen und in #865 weiterzumachen.

authors: alxndr-w eaCe marcohanke

license: MIT

license_source: github-api


text:
be_manager_relation mit relation table auf eine Tabelle

Ich habe versucht über eine Verknüpfungstabelle auf die gleiche Tabelle zu referenzieren, um eine "Siehe-auch"-Funktion zu implementieren.
Dabei wird aber das Relationsfeld in der Verknüpfungstabelle nicht gefüllt. Der Wert für die Verknüpfung wurde ins Feld für den Datensatz geschrieben, das Relationsfeld blieb leer.
$relationTableField['source'] und $relationTableField['target'] in be_manager_relation->postAction haben den gleichen Wert.

Kannst du mir die Feldkonfiguration als Screenshot posten?

Konfiguration für Items

Konfiguration für Item->Id

Konfiguration für Item->Relation

Ich habe es auch mit einem Patch hin bekommen, dass es funktioniert, stecke aber nicht tief genug im relation manager, als dass ich behaupte könnte, dass das die Lösung ist (bitte nicht nachmachen!).
Zeile 450 ff:
if (reset($source)->getName() == reset($target)->getName()) {
return array('source' => reset($source)->getName(), 'target' => next($target)->getName());
}

Verstehe. Es hätte vermutlich nur funktioniert, wenn du keine Relationstabelle verwendet hättest, sondern die IDs nur in das rex_wmv_items.see_also-Feld geschrieben hättest. Das hatte ich schon mal so benutzt.
Scheint also wirklich ein Bug zu sein.
Als Quick-and-Dirty-Lösung hättest du evtl. an der Datenbank eine VIEW zu rex_wmv_items erstellen können. Dann hättest du in der Relations-Tabelle zwei verschiedene Tabellen angeben können, statt 2x die gleiche zu verknüpfen. Dabei bliebe der Code von YForm unverändert und updatefähig.

authors: alexplusde dtpop


text:
Fix setting encoding for request options in downloadFileById.

Updated unit test.
Updated eslint version.
This fixes issue #15

Merging


text:
Emitter: Output space after an alias mapping key

Before:
a: &b x
*b: c

Now:
a: &b x
*b : c

Passing emitter tests:

E76Z: Aliases in Implicit Block Mapping
X38W: Aliases in Flow Objects

Test manually because make test-suite will overwrite changes in the skiplist:
./tests/run-parser-test-suite tests/run-test-suite/data/E76Z/in.yaml | ./tests/run-emitter-test-suite
./tests/run-parser-test-suite tests/run-test-suite/data/X38W/in.yaml | ./tests/run-emitter-test-suite

Or do:
(cd tests/run-test-suite; prove -lv test)

The semaphoreci failure seems to be testsuite related.
https://semaphoreci.com/ingydotnet/libyaml/branches/pull-request-185/builds/2

repo: yaml/libyaml


text:
Add a mandatory warning about unreachable conditions in @Binds  with multiple alternatives.

Let's consider the following code:
@Binds fun myApiWithMultipleImplementations(
    first: FirstImpl,
    second: SecondImpl
): MyApi

If  FirstImpl is under condition, that is implied by the SecondImpl's condition (or simply without condition) then the SecondImpl is unreachable and never will be bound to MyApi. This reasoning can be applied likewise to more than two alternatives.
It would be nice to warn the user about such situations, as it's most likely not what the user wanted to achieve.

The problem I found trying to implement this, is the fact, that a particular graph node can have different bindings in different graphs and thus have different conditions. In such case there might be a warning in terms of one graph, but no warning in terms of another graph.
Consider the example:
interface Api

@Conditional(onlyIn = [Product.Foo::class], condition = MyCondition::class]
@Conditional(onlyIn = [Product.Bar::class])  // unconditional in Bar
class Impl1 @Inject constructor() : Api

@Conditional(condition = MyAnotherCondition::class)
class Impl2 @Inject constructor(): Api

Then the following binding will be fully correct if included into a component with Product.Foo flavor, but should yield a warning about unreachable Impl2 in Product.Bar component:
@Binds fun api(i1: Impl1, i2: Impl2)

Such code is legit. Issuing a mandatory warning will force users to write dedicated bindings for each component and reduce DI-code sharing. And ideally speaking, there's probably nothing wrong with the binding above, it expresses the common order of alternatives, some of them may be unreachable in some components.
From the other hand, if the alternative is unreachable in every component, then the warning is certainly useful and would likely expose a real issue in the code. Sadly, we can't aggregate graphs across hierarchies as it's not supported by reflection and would penalize build speed in kapt/ksp.
So, there's no all the way nice solution here. It maybe possible to conceive a partial solution, though at the moment it's not what it would look like.

No clear solution on the annotation processing level is found, closing this

repo: yandex/yatagan


text:
This error will be reported as soon as the video is long

python scripts/demo.py --video_path /home/ubuntu/samurai/1643.mp4 --txt_path /home/ubuntu/1.txt
SAMURAI mode: True
Traceback (most recent call last):
File "/home/ubuntu/samurai/scripts/demo.py", line 122, in
main(args)
File "/home/ubuntu/samurai/scripts/demo.py", line 64, in main
height, width = loaded_frames[0].shape[:2]
IndexError: list index out of range
Thank you for reviewing my question

This error is caused by storing all frames of the video in one list, resulting in memory overflow. Trimming the video length and modifying the storage type can solve this problem

See https://github.com/facebookresearch/sam2/issues/264 for more details on inference long videos.


text:
🛑 Privatebin is down

In 0de902d, Privatebin (https://privatebin.icloudnative.io) was down:

HTTP code: 503
Response time: 5698 ms

Resolved: Privatebin is back up in 05edd98.

repo: yangchuansheng/upptime


text:
🛑 Umami is down

In e1f5b9b, Umami (https://umami.icloudnative.io) was down:

HTTP code: 503
Response time: 2000 ms

Resolved: Umami is back up in f7cf429.


text:
🛑 Google is down

In eca7bb1, Google (https://google.icloudnative.io) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Google is back up in 3a16d8e after 1,114 days, 5 hours, 15 minutes.


text:
🛑 Privatebin is down

In 3064450, Privatebin (https://privatebin.icloudnative.io) was down:

HTTP code: 503
Response time: 900 ms

Resolved: Privatebin is back up in fe48d77 after 6 minutes.


text:
Test PR for docs CI/CD (OK)

Should trigger docs rebuild (but not deploy) when the PR is opened.
Should trigger docs rebuild (and deploy) when the PR is merged,

Going to merge...

It worked! (tweaked docs on my gh pages)

repo: yanhasu/liquidhaskell


text:
am-editor-toolbar-vue2这个工具栏的包不能用呀！

1.vue2这个工具栏的包不能用
2.提供的demo跑不起来
3.急需工具栏插件，希望作者早日完成，感谢！
开源不易，作者加油呀！

demo 跑不起来能告知是有哪些问题吗？
包不能用，可能那边没有 build 就发布了吧，我给他说说

demo 跑不起来能告知是有哪些问题吗？ 包不能用，可能那边没有 build 就发布了吧，我给他说说

恩恩，toolbar明天我再看看能不能用，等您那边发布

demo 跑不起来能告知是有哪些问题吗？ 包不能用，可能那边没有 build 就发布了吧，我给他说说

用了toolbar-vue2这个包后报错  ：    TypeError: Object(...) is not a function
at Module. (index.esm.js:1363)
at Module../node_modules/am-editor-toolbar-vue2/dist/index.esm.js (index.esm.js:4440)
at webpack_require (bootstrap:766)
at fn (bootstrap:129)
at Object../node_modules/cache-loader/dist/cjs.js?!./node_modules/@vue/cli-plugin-babel/node_modules/babel-loader/lib/index.js!./node_modules/cache-loader/dist/cjs.js?!./node_modules/vue-loader/lib/index.js?!./src/components/preview/OfficePreview.vue?vue&type=script&lang=js&

可能需要使用 lerna bootstrap 命令把每个包的依赖加载进来

可能需要使用 lerna bootstrap 命令把每个包的依赖加载进来

但是我用yarn安装的呀，yarn要怎么解决呢，请问下

可能需要使用 lerna bootstrap 命令把每个包的依赖加载进来

方便加个qq 2530340502 把你们能跑起来的demo发我一份吗，带工具栏的。

https://github.com/zb201307/am-editor-vue2
这个就能跑起来呀
yarn
lerna bootstrap

https://github.com/zb201307/am-editor-vue2 这个就能跑起来呀 yarn
lerna bootstrap

恩恩，这样是可以的。但是我项目里面没有lerna，我用toolbar插件要怎么搞呀。本来想着装个包，引入组件就搞定了

重新装一下包，应该可以了

重新装一下包，应该可以了

重新装一下包，应该可以了

工具栏是可以显示了，但是工具栏是禁用状态，还有就是工具栏图标都显示为正方形。辛苦看下，感谢

提供复现或者截图吧，这边没复现。禁用状态可能是编辑器没有聚焦，或者你相应的插件没有引入

authors: JackFrancisLiu yanmao-cc

repo: yanmao-cc/am-editor


text:
design homepage

User story
As a user
I want to apply styling to the homepage
to reach the design-goal
Design/Wireframe

AC

[ ] the design should look like the design goal
[ ] the activity-cards should have the same design
[ ] the footer should consists of pictures/svgs
[ ] there should be a placeholder-image for the image-upload

Tasks

[ ] create new branch
[ ] replace the footer-text with svg's
[ ] add placeholder-image for info
[ ] apply global-style to background
[ ] use reusable design for activity-cards to lessen redundant code

Oh you are totally right. A user story makes more sense here. I will change it!

I'm sorry @yannhn , I think you need to make more changes than just change Value proposition from Developer to User, because the user don't know nothing about your design goals 😁
Example for the Value proposition
As I User
I want a intuitive and clear design
**So that **  it makes fun to use .... or something like that.
Example for the AC

the size of the button should be.... whatever
....

Please try again 🫣

authors: JessicaLoers yannhn

repo: yannhn/capstone-project


text:
[fix] jsx-no-undef: ignore namespaces

JSX namespaces are transpiled into strings, not identifiers.
This can be seen in here for TypeScript.
Babel behaves the same, but it requires a configuration which isn’t supported by their playground.

Codecov Report

Merging #2986 (9aa539d) into master (f864ac1) will decrease coverage by 0.00%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master    #2986      +/-   ##
==========================================
- Coverage   97.59%   97.59%   -0.01%
==========================================
  Files         110      110
  Lines        7269     7268       -1
  Branches     2651     2651
==========================================
- Hits         7094     7093       -1
  Misses        175      175

Impacted Files
Coverage Δ

lib/rules/jsx-no-undef.js
93.47% <100.00%> (-0.14%)
:arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update f864ac1...9aa539d. Read the comment docs.

authors: codecov-commenter remcohaszing

repo: yannickcr/eslint-plugin-react


text:
IO工具问题

Actual test found,!=-1 in some cases will cause an infinite loop, which will make the entire frame unable to continue running. Replace it with >. 0 can be solved.
实际测试发现，!=-1在部分情况下会导致死循环，使整个框架无法继续运行，替换成>0可解决。

你好，非常感谢参与开源项目。
InputStream.read(byte[] b)方法有以下特点：

当b的长度为0时，不读取任何字段，并返回长度为0。
当b的长度大于0时，至少会尝试读取一个字节，并返回读取到的总字节数。
如果没有字节可用，或者已到流的末尾，则返回-1。

InputStream.read()方法有以下特点：

读取流中的数据的下一个字节并返回，因此返回值可能是0-255中的任何值。
如果没有字节可用，或者已到流的末尾，则返回-1。

综上，源代码的写法没有问题，而pr的代码忽略了0这个值。

authors: lucifinilsu yanzhenjie

repo: yanzhenjie/Kalle


text:
Optimize git push and API requests

When the number of patches in a stack grows beyond just a few, the time it takes for gerritlab to perform its operations can become very long (30 seconds or more).
This commit attempts to improve the situation by making the following changes:

Use a single git push to push all commits to their respective branches.  This is a major time saver.

Determine whether an MR needs to be updated or created using only the information returned by merge_request.get_all_merge_requests(). Never perform additional MR queries.

This commit removes the old logic that was required to deal with unexpected GitLab auto-merge behavior (FIXME: reference needed).  That problem doesn't seem to happen anymore, which is good because now the code can be much simpler.
There's a lot of debugging/profiling stuff left in this commit that needs to be removed before finalizing.

Ready for re-review.

LGTM!

authors: dancysoft yaoyuannnn

repo: yaoyuannnn/gerritlab


text:
useHashtag not working

I cannot get it working with col-pick-input

That's because the current 0.5.0 version does not contain last fixes in the master branch.
@lukemelia: Can you release a new version?

@jevanlingen Released 0.6.0. Thanks!

authors: jevanlingen lukemelia mmahalwy

repo: yapplabs/ember-colpick


text:
How to enable LovelyInfoDialog that has been set to not show again?

Is there a way to enable what has been checked to not show again in the LovelyInfoDialog to show up again with the 'Do not show agaiN' unchecked?

Hi. Use
LovelyInfoDialog.reset(context, idYouPassToSetNotShowAgainOptionEnabled);

repo: yarolegovich/LovelyDialog


text:
Add a way to write the BOM that Excel likes to read the csv properly

It's maybe not the best of the best in the CSV world, but Excel likes to have a BOM at the beginning of the file to read it properly. It could be a good idea to add an option to write it, since there is already an implementation to read it.
For now, I'm using as a quick "hack" to make the CSV look good in Excel:
let csv = try CSVWriter(...codecType: UTF8.self,...)
csv.stream.write([0xef, 0xbb, 0xbf], maxLength: 3) // UnicodeBOM.utf8

@GregOriol could you explain better your work-around, I'm facing the same issue.

@RafaelPlantard Not sure what you need more here :-) Create the new writer instance with the codecType as in my example, add the line to write to BOM as in my example and then write your data as usual/as described in the readme of the project.

@GregOriol you write this before each line or only before the first line:
csv.stream.write([0xef, 0xbb, 0xbf], maxLength: 3) // UnicodeBOM.utf8
?

@RafaelPlantard Only once! The BOM (ie. those 3 special chars) should be at the very beginning of the file

authors: GregOriol RafaelPlantard


text:
spring integration

Hi,
Do you have any idea to integrate the crawler with spring? Or do i have to check out the code and edit by myself(and also i wont be able to get your updates)?

You can implement a WebCrawlerFactory, which is Spring-based and pass this implementation into the CrawlController.

This is documented in the README:
https://github.com/yasserg/crawler4j#using-a-factory


text:
Update bower to use the latest release

Currently bower refers to 1.0.3, but it seems that the latest tag is 1.1.2 according to the download page.

Could you please justify?

This library use closure tool. It is not compatible (or require a lot of maintenance work) with bower. It is not only bower, there are npm, browisify.

authors: FMCorz yathit

repo: yathit/ydn-db


text:
MongoDB mounted volume is broken

MongoDB uses mounted elastic volume.  Production and development use different volumes of course but there's no way to identify, and it looks like deploying new dev environment breaks production volume.

Fixed in asobann_deploy repository.
https://github.com/yattom/asobann_deploy/commit/03891181a334b73be915fa9f2f6df0984c48c1ce


text:
Add theme color (Android 5)

Op verzoek van Anthe een thema kleur toevoegen.

Werkt alleen voor Google Chrome.

Nee, werkt voor veel browsers die ernaar luisteren. Het is intussen een voorgestelde standaard, hoewel ik niet zeker weet of hij al geaccepteerd is en doorgevoerd wordt in andere browsers.

Oh, dat wist ik niet, geweldig!

authors: Robbai WoutervdBrink

repo: yayscripting/smf-smartphone


text:
feat: implement query service

With two methods:

Query("query text", query_params, optional transaction mode, lambda (result stream))
QueryTx(optional transaction mode, lambda(tx))

lambda is retriable user callback. When use queryTx - transaction will commit by default and has way for rollback (exception + tx.Rollback()).
And see to spanner.
Roadmap:

[ ] Implement .Query() - method for single SQL execution without transaction creation
[ ] Implement .QueryTx() method for multiple SQL executions on same transaction
waiting for Begin/Commit/Rollback transaction methods will be realized on server (at the moment transactions works using TableService methods)
[ ] Session attach/detach
[ ] Merge implementation of SessionPools from Query and Table services

[ ] Attach
[ ] Detach

[ ] Retryer
[ ] Examples
[ ] helper methods such as Select, SelectFirstOrDefault, NonQuery etc.

The first implementation was extremely unsuccessful.

authors: KirillKurdyukov rekby

repo: ydb-platform/ydb-dotnet-sdk


text:
Pr ft server status

add LspServerStatus(ft) func to detect ft lsp server was running or not (or not found)

just like LspServerReady() func for ready but this one for (checking if it is) running (or not).
// this was created for #5
--
shane.xb.qian

renamed as your suggested.

repo: yegappan/lsp


text:
TiffCompression.jpeg support for decode

It would appear that the TiffCompression.jpeg is not supported.
Any plans to support this, I got an error on the first multipage tiff I tried to decode as a result of this throw, tiff-image.js@551.

To be honest, I can try to look at it when I have time, but I'm not sure if it can be done quickly, and if it can be done at all in the near future.
But could you please provide an example file of such an image that you have a problem with? Thank you!

Hi @kariudo!
To be honest, I can try to look at it when I have time, but I'm not sure if it can be done quickly, and if it can be done at all in the near future.
But could you please provide an example file of such an image that you have a problem with? Thank you!

authors: kariudo yegor-pelykh

repo: yegor-pelykh/image-in-browser


text:
Weekly check links

ref: #80

@yegor256 take a look please

@blablatdinov thanks!


text:
RqMultipart is not supporting multiple file transfer

There is no code to produce valid request collections on multiple file transfer.

@d-molotchko I'm not sure I follow.. could you please explain more and provide some Java code sample that fails at the moment

@yegor256 Quote from http://www.w3.org/TR/html401/interact/forms.html#h-17.13.4.2 is

If multiple files are to be returned as the result of a single form entry, they should be returned as "multipart/mixed" embedded within the "multipart/form-data".

But I can't reproduce this behavior with chrome 40 and iceweasel 31.4

@d-molotchko I still don't understand where is our bug. How can I reproduce it? Show me the Java code please.

I can't generate request with nested sections in my browsers, maybe this behavior is out of date.
There is syntetic test for nested sections
public final class RqMultipartTest {

    /**
     * RqMultipart can parse body.
     * @throws IOException If some problem inside
     */
    @Test
    public void parsesHttpBody() throws IOException {
        final Request req = new RqFake(
            Arrays.asList(
                "POST /h?a=3 HTTP/1.1",
                "Host: www.example.com",
                "Content-Type: multipart/form-data; boundary=AaB03x",
                "Content-Length: 10000"
            ),
            Joiner.on("\r\n").join(
                "--AaB03x",
                "Content-Disposition: form-data; name=\"address\"",
                "",
                "440 N Wolfe Rd, Sunnyvale, CA 94085",
                "--AaB03x",
                // @checkstyle LineLength (1 line)
                "Content-Disposition: form-data; name=\"files\"",
                "Content-Type: multipart/mixed; boundary=BbC04y",
                "",
                "--BbC04y",
                "Content-Disposition: file; filename=\"file1.txt\"",
                "Content-Type: text/plain",
                "",
                "first file content",
                "--BbC04y",
                "Content-Disposition: file; filename=\"file2.gif\"",
                "Content-Type: text/plain",
                "",
                "second file content",
                "--BbC04y--",
                "--AaB03x--"
            )
        );
        final RqMultipart multi = new RqMultipart(req);
        final Iterator<Request> it = multi.part("files").iterator();
        MatcherAssert.assertThat(
            new RqPrint(
                it.next()
            ).printBody(),
            Matchers.equalTo("first file content")
        );
        MatcherAssert.assertThat(
                new RqPrint(
                    it.next()
                ).printBody(),
                Matchers.equalTo("second file content")
            );
    }
}

@d-molotchko looks like we need a new class RqMultipartMixed for parsing these requests and it would work like this:
Request files = multi.part("files").iterator().next();
Request first = new RqMultipartMixed(files).part("file1.txt").iterator().next();
Request second = new RqMultipartMixed(files).part("file2.gif").iterator().next();

make sense?

@yegor256 maybe like this?
Request files = multi.part("files").iterator().next();
Iterator<Request> it = new RqMultipartMixed(files).iterator();
Request first = it.next();
Request second = it.next();

There are no file names in compile time .

@d-molotchko yes, right

@d-molotchko I think that in order to reproduce this request in a browser we should use multiple attribute (see http://www.w3.org/TR/html-markup/input.file.html):
<input type="file" name="foo" multiple />

@yegor256 I try this
<INPUT type="file" name="file[]" multiple >

but fail

@d-molotchko what you mean by "fail"? what is the request you're getting from the browser?

"fail" is "I didn't get multipart/mixed content from browser".
Chrome and Iceweasel returns multiple files without multipart/mixed section.

@d-molotchko can you post an entire request here?

POST / HTTP/1.1
Host: localhost
Connection: keep-alive
Content-Length: 4204
Content-Type: multipart/form-data; boundary=----WebKitFormBoundaryYAyERkBAWwbSXVxh

------WebKitFormBoundaryYAyERkBAWwbSXVxh
Content-Disposition: form-data; name="submit-name"

John
------WebKitFormBoundaryYAyERkBAWwbSXVxh
Content-Disposition: form-data; name="file[]"; filename="RqMethodTest.java"
Content-Type: text/x-java

------WebKitFormBoundaryYAyERkBAWwbSXVxh
Content-Disposition: form-data; name="file[]"; filename="RqWithoutHeaderTest.java"
Content-Type: text/x-java

------WebKitFormBoundaryYAyERkBAWwbSXVxh--

@d-molotchko maybe this multipart/mixed packaging is outdated and shouldn't be supported by us? Why did you decide to report this issue? How did you get stuck on it?

@yegor256 maybe, I don't know. I decide to report this issue because refactor RqMultipart code and see request example on link above. HTML 4.01 is pretty actual version of standard. Any way, you decide what to do with it. Leave as is. New issue is created in few minutes.

@d-molotchko let's keep this ticket open for some time and see whether anyone else will report a similar problem. For now I don't see a reason to implement all this, since Chrome is not using this multipart/mixed content type.

@d-molotchko I'm closing this one as no one reported a similar problem in the last two years.

Job gh:yegor256/takes#141 is not assigned, can't get performer

This job is not in scope


text:
Body.java:41-45: Make Body extends Cactoos's Input and...

The puzzle 804-84fdf636 from #804 has to be resolved:
https://github.com/yegor256/takes/blob/1d43de35261ec3d5a3ee11ce6f156e35a752131a/src/main/java/org/takes/rs/Body.java#L41-L45
The puzzle was created by Victor Noël on 24-Nov-18.
If you have any technical questions, don't ask me, submit new tickets instead. The task will be "done" when the problem is fixed and the text of the puzzle is removed from the source code. Here is more about PDD and about me.

@paulodamaso/z please, pay attention to this issue

Job #887 is now in scope, role is DEV


text:
Could not load dynamic library 'libcudart.so.11.0'; dlerror:

您好，我发现在程序没有停止运行的情况下，遇到以下一些(截取了部分) error，在运行 log 中通常标记为 W，请问这些报错是为什么呢？是否会影响结果，谢谢！
Total processed positions in Chr2h00 (chunk 5/6) : 65085
Total time elapsed: 205.46 s
2022-12-09 16:44:06.651759: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-12-09 16:44:07.597312: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2022-12-09 16:44:07.597403: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2022-12-09 16:44:09.659883: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2022-12-09 16:44:09.660136: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2022-12-09 16:44:09.660169: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2022-12-09 16:44:14.087976: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2022-12-09 16:44:14.088681: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2022-12-09 16:44:14.088953: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (wxw-Super-Server): /proc/driver/nvidia/version does not exist
2022-12-09 16:44:14.091689: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Calling variants ...
Total processed positions in Chr2h00 (chunk 6/6) : 65146
Total time elapsed: 209.73 s
2022-12-09 16:43:33.529776: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-12-09 16:43:33.897579: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2022-12-09 16:43:33.897709: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2022-12-09 16:43:38.317267: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2022-12-09 16:43:38.318458: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2022-12-09 16:43:38.318650: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2022-12-09 16:43:43.359557: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2022-12-09 16:43:43.359668: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2022-12-09 16:43:43.359720: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (wxw-Super-Server): /proc/driver/nvidia/version does not exist
2022-12-09 16:43:43.360174: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Calling variants ...
Total processed positions in Chr2h18 (chunk 2/4) : 63390
Total time elapsed: 241.85 s
2022-12-09 16:43:48.758377: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-12-09 16:43:50.615858: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2022-12-09 16:43:50.616531: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2022-12-09 16:43:52.739768: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2022-12-09 16:43:52.740052: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2022-12-09 16:43:52.740090: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2022-12-09 16:43:57.225463: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2022-12-09 16:43:57.226372: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2022-12-09 16:43:57.226688: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (wxw-Super-Server): /proc/driver/nvidia/version does not exist
2022-12-09 16:43:57.230685: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Calling variants ...
Total processed positions in Chr2h18 (chunk 4/4) : 69829
Total time elapsed: 238.72 s

real	24m31.352s
user	668m49.375s
sys	37m54.743s

Hi Xiaowen,
I am wondering if you are using conda to directly install duet, or you are installing other dependencies first and then using pip to isntall duet. If the latter, I suggest you to reinstall duet by conda and try again.
conda env remove -n duet
conda config --add channels bioconda && conda config --add channels conda-forge
conda create -n duet -c bioconda duet -y && conda activate duet

Let me know if it works well.
Yekai

Dear Xiaowen,
Normally this is because of some version differences between your preinstalled tensorflow/cuda to the versions that duet used in Clair3. These warnings normally do not affect the results. Did you get the resulting variant calls in the snp_calling folder? If so I think you can safely proceed.
Yekai

authors: luckyvivi yekaizhou

repo: yekaizhou/duet


text:
isValidIpPort too restrictive

I'm attempting to set up your repository as part of docker-compose environment. When testing the connection during the installation step, I ran into issues related to the isValidIpPort function. This issue comes from the fact that, given the docker-compose environment, the host can be given any string name the user declares inside the docker-compose.yml file.  To solve this issue I had to manually remove the isValidIpPort call from the if-statement. Attached is an example of how the installation form could be filled out in an docker-compose environment.

If you'd like I can contribute my Dockerfile and make minor changes to index.php inside the installation folder and send them your way via a PR.
Thank you for your awesome work!

Hello, nice catch; I will modify the function to detect if its in docker env and act accordingly. Dockerfile would be nice :)

authors: christophbrosch yesilmen-vm

repo: yesilmen-vm/YesilCMS


text:
Fix HtmlSelect not resetting properly when value changed

Add Reset button to HtmlSelect example & small refactor
Fix HtmlSelect not resetting properly when value changed
Remove unnecessary macro

:heavy_check_mark:  Self approving myself on my own

repo: yewprint/yewprint


text:
boilerplate for typescript migration

The CI is expected to not pass here. Source code changes necessary to get the build + tests working will come in an following PR.

use cjs-to-es6 to change all imports/exports from require() to import, a number of requires() and module.exports/exports had to be manually patched due to us using less typical syntax
renames all files under src from .js to .ts, and adds tsconfig. Since we restrict to node 12 and up, we can use target: "es2019", lib: "es2019" for things like array.prototype.flatMap (which we already use)
adds babel.config.js so that jest can understand es6 and typescript, and updates eslint config
adds npm dependencies like @handlebars/parser, babel-jest, and other typescriptey things (also updates yargs + jest),

J=SLAP-1491
TEST=manual
smoke test jambo (with the upcoming PRs included)

It's a little odd to me that #239 is showing up in this diff. Would that go away if we merged #239 into feature/typescript-migration first? Otherwise, LGTM

It's a little odd to me that #239 is showing up in this diff. Would that go away if we merged #239 into feature/typescript-migration first? Otherwise, LGTM

239 has already been merged in (by merging develop into this branch), I think I can fix it by rebasing though

It's a little odd to me that #239 is showing up in this diff. Would that go away if we merged #239 into feature/typescript-migration first? Otherwise, LGTM

~239 has already been merged in (by merging develop into this branch), I think I can fix it by rebasing though~
ah nevermind I thought you meant merge into the dev branch not feature branch, I think that would have worked
I rebased both the dev and feature branch but it still shows up as changed, I think this is a bug in github because if I make a new pull request with the same 2 branches in the changed files it displays as expected

Alright, I think we're fine then. When we merge this feature branch into develop I think that part of the diff will go away

repo: yext/jambo


text:
The last slide is not displayed from the second loop when there are exactly 2 slides

Describe the bug
The last slide is not displayed from the second loop in carousel with loop when there are exactly 2 slides.
To Reproduce
Steps to reproduce the behavior:

Make a carousel with loop and with 2 slides
Click on the right arrow button to loop all slides once
Click on the right arrow button to go to the last slide
See the error that the last slide is not displayed

Expected behavior
The last image should be display at the last index.
Screenshots
The GIF below is taken from the initial loading to the occurrence of the bug.

Desktop (please complete the following information):

macOS
Chrome
Version 89.0.4389.90 (Official Build) (x86_64)

又是我！😂 I also have this problem!

I am sorry to hear that! Please rest assured that I have fixed it on my machine. I will release an update today. 😉

This issue is now fixed in v0.1.2

Here is the carousel to show that the bug is fixed.
The GIF below is taken from the initial loading to the place where the bug had occurred.

authors: Lewis-Seekio yifaneye

repo: yifaneye/react-gallery-carousel


text:
Setting YII_DEBUG=false in humhub 1.15.2 leads to internal server error

What steps will reproduce the problem?
Setting YII_DEBUG=false in index.php in humhub root directory quickly leads to internal server error.
What is the expected result?
Humhub should operate normal and in production mode.
What do you get instead?
Internal server error, which is resolved immediately when setting YII_DEBUG back to true.
Additional info

Q
A

Yii version
Yii v2.0.50-dev

PHP version
8.2

Operating system
Linux ae93c 5.10.0-26-amd64 #1 SMP Debian 5.10.197-1 (2023-09-29) x86_64 GNU/Linux

Env
Netcup webhosting / plesk

Full context;
https://github.com/humhub/humhub/issues/6846

I don't think there's anything to fix in the framework itself regarding the error encountered.

authors: ArchBlood samdark ukaeufe


text:
Suggestion: Is any chance to see in Yii2 the following useful console commands like Symfony2 has?

Suggestion: Is any chance to see in Yii2 the following useful console commands like Symfony2 has?
for example like this from Symfony2:
help                Display help for a command
list                Lists all registered console commands
assetic:dump        Dumps all assets to the file system
cache:clear         Clear the cache
cache:warmup        Warms up an empty cache
route:debug         Dysplay current routes for an application
(route:dump-apache   Dumps all routes as Apache rewrite rules)
route:match         Helps debug routes by simulating a path info match
(server:run          Run PHP built-in web server)
(translation:update  Updates the translation file)

Yii2 uses controllers for the commands so I think we can create a HelpController that simply reads the phpDoc.
yii help migrate/create
Would read the phpDoc of MigrateController class and actionCreate method

@Faryshta have you tried to run that command, it already works that way ;)
@uran1980 many of the mentioned commands are already available. Which exactly do you miss?

$ ./yii

This is Yii version 2.0.3-dev.

The following commands are available:

- asset     Allows you to combine and compress your JavaScript and CSS files.
- cache     Allows you to flush cache.
- fixture   Manages fixture data loading and unloading.
- help      Provides help information about console commands.
- message   Extracts messages to be translated from source files.
- migrate   Manages application migrations.

To see the help of each command, enter:

  yii help <command-name>

thats very cool, i didn't knew the existance of help command or any of the others, we need a section of available commands on the docs
http://www.yiiframework.com/doc-2.0/guide-tutorial-console.html

And i think list all sub commands on top view is will good to use.
Like
$ ./yii

This is Yii version 2.0.3-dev.

The following commands are available:

- asset     Allows you to combine and compress your JavaScript and CSS files.
	- asset/compress (default): Combines and compresses the asset files according to the given configuration.
	- asset/template: Creates template of configuration file for [[actionCompress]].

- cache     Allows you to flush cache.
	- cache/flush: Flushes given cache components.
	- cache/flush-all: Flushes all caches registered in the system.
	- cache/flush-schema: Clears DB schema cache for a given connection component.
	- cache/index: Lists the caches that can be flushed.

- fixture   Manages fixture data loading and unloading.
	- fixture/load: Loads the specified fixture data.
	- fixture/unload: Unloads the specified fixtures.

- gii       This is the command line version of Gii - a code generator.
	- gii/controller: Controller Generator
	- gii/crud: CRUD Generator
	- gii/extension: Extension Generator
	- gii/form: Form Generator
	- gii/index
	- gii/model: Model Generator
	- gii/module: Module Generator

- help      Provides help information about console commands.

- message   Extracts messages to be translated from source files.
	- message/config: Creates a configuration file for the "extract" command.
	- message/extract: Extracts messages to be translated from source code.

- migrate   Manages application migrations.
	- migrate/create: Creates a new migration.
	- migrate/down: Downgrades the application by reverting old migrations.
	- migrate/history: Displays the migration history.
	- migrate/mark: Modifies the migration history to the specified version.
	- migrate/new: Displays the un-applied new migrations.
	- migrate/redo: Redoes the last few migrations.
	- migrate/to: Upgrades or downgrades till the specified version.
	- migrate/up: Upgrades the application by applying new migrations.

To see the help of each command, enter:

Good idea @callmez. Want to work on adding it?

ok, will try to PR later

In the real world, it's likely you will have tens of commands. Expanding the subcommands by default will result in a super long list of output.

Imagine the real use scenario: when you want to execute a command, you first want to find out which kind of command you want to execute, then you will identify which sub-command to execute. Expanding all sub-command together will make the first step more difficult.

even though the list is long what you really want is the subcommand that is available so that you can run it. The current list of main commands is not very helpful as you may run them in some cases and in some cases not. This is not obvious from the current list. To actually run a command you currently always have to run the help two times to be sure what command you want to run. When all are listed you get your goal right away. I am for adding sub commands in the list.

In fact most web apps doesn't have tens of commands, developers just want to know what command can  be use

commands available can be tricky because since the commands are controllers they can be added in modules, apps or by other packages and libraries installed with composer.
for example in production environment gii is not available. I think it would be better if ./yii is simply a shortcut for ./yii help

I think long list is OK. Console buffer is long enough usually so you can scroll to read it.

authors: Faryshta callmez cebe qiangxue samdark uran1980


text:
Automatically clear Session table in database

Is there any workaround to automatically clear session table mentioned on this page:
http://www.yiiframework.com/doc-2.0/guide-runtime-sessions-cookies.html
It's becoming huger and huger by the time.

There is an expiry time in the table, which should be automatically cause the Entry to be removed. Do you have expiry times that are far in the past but still stored in the table?

Closed since there is no response from the author.

Good answer about this topic: https://stackoverflow.com/a/34310472/5707560

authors: cebe egorsmkv klimov-paul turalus


text:
Disable serialization by default for ArrayCache for increased performance

Q
A

Is bugfix?
no

New feature?
no

Breaks BC?
yes

Tests pass?
yes

Fixed issues
-

I would expect the ArrayCache to be optimized for speed since it's only used during a single requests, but the serialization is turned on by default which has a major performance impact (see test below).
Turning the serialization off might brake backwards compatibilty due to the check in the yii/caching/Cache class: if ($dependency !== null && $this->serializer !== false) {
Test results:
unserialized: 9.3 ms
serialized: 3391.6 ms
Test data: two dimensional array (100x100)
Test run: 100 x 1 write, 10 reads
Test:
$data = array_fill(0, 100, array_fill(0, 100, rand(0, 10000)));

Yii::$app->arrayCache->serializer = false;
Yii::beginProfile('cacheTest-unserialized');
for ($i = 1; $i <= 100; $i++) {
    Yii::$app->arrayCache->set("cacheTest-unserialized-$i", $data);
    for ($j = 1; $j <= 10; $j++) {
        Yii::$app->arrayCache->get("cacheTest-unserialized-$i");
    }
}
Yii::endProfile('cacheTest-unserialized');

Yii::$app->arrayCache->serializer = null;
Yii::beginProfile('cacheTest-serialized');
for ($i = 1; $i <= 100; $i++) {
    Yii::$app->arrayCache->set("cacheTest-serialized-$i", $data);
    for ($j = 1; $j <= 10; $j++) {
        Yii::$app->arrayCache->get("cacheTest-serialized-$i");
    }
}
Yii::endProfile('cacheTest-serialized');

Makes sense. Voting for.

agree. Optimal performance should be the default.

No need to break anything here. This can be added as a note in the class PHPdoc and can be enabled if needed. ArrayCache has very rare use cases anyway.

I'm against merging this change. It makes default behavior very inconsistent. Instead, I'd mention it in either performance guide or the ArrayCache class itself.

I have added a note to the class docs. performance improvement is not an acceptable reason for BC breaks. Thanks for your contribution, @rhertogh!

authors: SilverFire cebe dynasource rhertogh samdark


text:
Fixed saving empty records with default PK values in MySQL

Q
A

Is bugfix?
✔

New feature?
❌

Breaks BC?
❌

Fixed issues
#15500

This change will use NULL instead of DEFAULT for PK columns on saving empty records into a table.

Thanks

authors: manchenkoff samdark