[jira] [Created] (SPARK-4425) Handle NaN cast to Timestamp correctly
Takuya Ueshin created SPARK-4425: Summary: Handle NaN cast to Timestamp correctly Key: SPARK-4425 URL: https://issues.apache.org/jira/browse/SPARK-4425 Project: Spark Issue Type: Bug Components: SQL Reporter: Takuya Ueshin {{Cast}} from {{NaN}} or {{Infinity}} of {{Double}} or {{Float}} to {{TimestampType}} throws {{NumberFormatException}}. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-4425) Handle NaN or Infinity cast to Timestamp correctly
[ https://issues.apache.org/jira/browse/SPARK-4425?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Takuya Ueshin updated SPARK-4425: - Summary: Handle NaN or Infinity cast to Timestamp correctly (was: Handle NaN cast to Timestamp correctly) Handle NaN or Infinity cast to Timestamp correctly -- Key: SPARK-4425 URL: https://issues.apache.org/jira/browse/SPARK-4425 Project: Spark Issue Type: Bug Components: SQL Reporter: Takuya Ueshin {{Cast}} from {{NaN}} or {{Infinity}} of {{Double}} or {{Float}} to {{TimestampType}} throws {{NumberFormatException}}. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4425) Handle NaN or Infinity cast to Timestamp correctly
[ https://issues.apache.org/jira/browse/SPARK-4425?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213452#comment-14213452 ] Apache Spark commented on SPARK-4425: - User 'ueshin' has created a pull request for this issue: https://github.com/apache/spark/pull/3283 Handle NaN or Infinity cast to Timestamp correctly -- Key: SPARK-4425 URL: https://issues.apache.org/jira/browse/SPARK-4425 Project: Spark Issue Type: Bug Components: SQL Reporter: Takuya Ueshin {{Cast}} from {{NaN}} or {{Infinity}} of {{Double}} or {{Float}} to {{TimestampType}} throws {{NumberFormatException}}. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-4426) The symbol of BitwiseOr is wrong, should not be ''
Kousuke Saruta created SPARK-4426: - Summary: The symbol of BitwiseOr is wrong, should not be '' Key: SPARK-4426 URL: https://issues.apache.org/jira/browse/SPARK-4426 Project: Spark Issue Type: Bug Components: SQL Affects Versions: 1.3.0 Reporter: Kousuke Saruta Priority: Minor The symbol of BitwiseOr is defined as '' but I think it's wrong. It should be '|'. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4426) The symbol of BitwiseOr is wrong, should not be ''
[ https://issues.apache.org/jira/browse/SPARK-4426?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213472#comment-14213472 ] Apache Spark commented on SPARK-4426: - User 'sarutak' has created a pull request for this issue: https://github.com/apache/spark/pull/3284 The symbol of BitwiseOr is wrong, should not be '' --- Key: SPARK-4426 URL: https://issues.apache.org/jira/browse/SPARK-4426 Project: Spark Issue Type: Bug Components: SQL Affects Versions: 1.3.0 Reporter: Kousuke Saruta Priority: Minor The symbol of BitwiseOr is defined as '' but I think it's wrong. It should be '|'. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-4427) In Spark Streaming when we perform window operations , it wil caluclate based on system time, i need to override it, i mean instead of getting current time app need to
ch.prasad created SPARK-4427: Summary: In Spark Streaming when we perform window operations , it wil caluclate based on system time, i need to override it, i mean instead of getting current time app need to get from my text file. Key: SPARK-4427 URL: https://issues.apache.org/jira/browse/SPARK-4427 Project: Spark Issue Type: Bug Reporter: ch.prasad Please provide solution asap. in window operation wen we give window size, it get data from rdd's by caluclating window size with current time , i need to change current time , to be read from my file. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4426) The symbol of BitwiseOr is wrong, should not be ''
[ https://issues.apache.org/jira/browse/SPARK-4426?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213567#comment-14213567 ] ch.prasad commented on SPARK-4426: -- please see my issue .. i hope all of you! SPARK-4427 thanks..! The symbol of BitwiseOr is wrong, should not be '' --- Key: SPARK-4426 URL: https://issues.apache.org/jira/browse/SPARK-4426 Project: Spark Issue Type: Bug Components: SQL Affects Versions: 1.3.0 Reporter: Kousuke Saruta Priority: Minor The symbol of BitwiseOr is defined as '' but I think it's wrong. It should be '|'. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-4428) Use ${scala.binary.version} property for artifactId.
Takuya Ueshin created SPARK-4428: Summary: Use ${scala.binary.version} property for artifactId. Key: SPARK-4428 URL: https://issues.apache.org/jira/browse/SPARK-4428 Project: Spark Issue Type: Bug Components: Build Reporter: Takuya Ueshin -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4428) Use ${scala.binary.version} property for artifactId.
[ https://issues.apache.org/jira/browse/SPARK-4428?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213593#comment-14213593 ] Apache Spark commented on SPARK-4428: - User 'ueshin' has created a pull request for this issue: https://github.com/apache/spark/pull/3285 Use ${scala.binary.version} property for artifactId. Key: SPARK-4428 URL: https://issues.apache.org/jira/browse/SPARK-4428 Project: Spark Issue Type: Bug Components: Build Reporter: Takuya Ueshin -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Closed] (SPARK-4403) Elastic allocation(spark.dynamicAllocation.enabled) results in task never being execued.
[ https://issues.apache.org/jira/browse/SPARK-4403?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Egor Pahomov closed SPARK-4403. --- Resolution: Invalid Elastic allocation(spark.dynamicAllocation.enabled) results in task never being execued. Key: SPARK-4403 URL: https://issues.apache.org/jira/browse/SPARK-4403 Project: Spark Issue Type: Bug Components: Spark Core, YARN Affects Versions: 1.1.1 Reporter: Egor Pahomov Attachments: ipython_out I execute ipython notebook + pyspark with spark.dynamicAllocation.enabled = true. Task never ends. Code: {code} import sys from random import random from operator import add partitions = 10 n = 10 * partitions def f(_): x = random() * 2 - 1 y = random() * 2 - 1 return 1 if x ** 2 + y ** 2 1 else 0 count = sc.parallelize(xrange(1, n + 1), partitions).map(f).reduce(add) print Pi is roughly %f % (4.0 * count / n) {code} {code} IPYTHON_ARGS=notebook --profile=ydf --port $IPYTHON_PORT --port-retries=0 --ip='*' --no-browser pyspark \ --verbose \ --master yarn-client \ --conf spark.driver.port=$((RANDOM_PORT + 2)) \ --conf spark.broadcast.port=$((RANDOM_PORT + 3)) \ --conf spark.replClassServer.port=$((RANDOM_PORT + 4)) \ --conf spark.blockManager.port=$((RANDOM_PORT + 5)) \ --conf spark.executor.port=$((RANDOM_PORT + 6)) \ --conf spark.fileserver.port=$((RANDOM_PORT + 7)) \ --conf spark.shuffle.service.enabled=true \ --conf spark.dynamicAllocation.enabled=true \ --conf spark.dynamicAllocation.minExecutors=1 \ --conf spark.dynamicAllocation.maxExecutors=10 \ --conf spark.ui.port=$SPARK_UI_PORT {code} -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-4429) Build for Scala 2.11 using sbt fails.
Takuya Ueshin created SPARK-4429: Summary: Build for Scala 2.11 using sbt fails. Key: SPARK-4429 URL: https://issues.apache.org/jira/browse/SPARK-4429 Project: Spark Issue Type: Bug Components: Build Reporter: Takuya Ueshin I tried to build for Scala 2.11 using sbt with the following command: {quote} $ sbt/sbt -Dscala-2.11 assembly {quote} but it ends with the following error messages: {quote} \[error\] (streaming-kafka/*:update) sbt.ResolveException: unresolved dependency: org.apache.kafka#kafka_2.11;0.8.0: not found \[error\] (catalyst/*:update) sbt.ResolveException: unresolved dependency: org.scalamacros#quasiquotes_2.11;2.0.1: not found {quote} -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Resolved] (SPARK-4427) In Spark Streaming when we perform window operations , it wil caluclate based on system time, i need to override it, i mean instead of getting current time app need to
[ https://issues.apache.org/jira/browse/SPARK-4427?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Sean Owen resolved SPARK-4427. -- Resolution: Invalid JIRAs are for reporting specific issues and proposing changes. This is a question, so would be better asked on the mailing list. I suggest you reword the question though to be more complete and specific as it's not quite clear what the issue is. In Spark Streaming when we perform window operations , it wil caluclate based on system time, i need to override it, i mean instead of getting current time app need to get from my text file. Key: SPARK-4427 URL: https://issues.apache.org/jira/browse/SPARK-4427 Project: Spark Issue Type: Bug Reporter: ch.prasad Original Estimate: 24h Remaining Estimate: 24h Please provide solution asap. in window operation wen we give window size, it get data from rdd's by caluclating window size with current time , i need to change current time , to be read from my file. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4428) Use ${scala.binary.version} property for artifactId.
[ https://issues.apache.org/jira/browse/SPARK-4428?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213664#comment-14213664 ] Mark Hamstra commented on SPARK-4428: - This is not a bug, nor is it a major issue, nor is parameterizing artifactId's in this way permissible. This is a Won't Fix. Use ${scala.binary.version} property for artifactId. Key: SPARK-4428 URL: https://issues.apache.org/jira/browse/SPARK-4428 Project: Spark Issue Type: Bug Components: Build Reporter: Takuya Ueshin -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Resolved] (SPARK-4428) Use ${scala.binary.version} property for artifactId.
[ https://issues.apache.org/jira/browse/SPARK-4428?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Mark Hamstra resolved SPARK-4428. - Resolution: Won't Fix Use ${scala.binary.version} property for artifactId. Key: SPARK-4428 URL: https://issues.apache.org/jira/browse/SPARK-4428 Project: Spark Issue Type: Bug Components: Build Reporter: Takuya Ueshin -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4402) Output path validation of an action statement resulting in runtime exception
[ https://issues.apache.org/jira/browse/SPARK-4402?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213729#comment-14213729 ] Vijay commented on SPARK-4402: -- Thanks for the reply [~srowen] This is different scenario from the issue SPARK-1100. Issue SPARK-1100 says that output directory is over written if it exists. I think that fix works fine. But, my concern is that spark throws a runtime exception if the output directory exists. This is happening after executing all the previous action statements and resulting in abrupt termination of the program. Result of the previous action statements is lost. Please confirm whether this abrupt program termination is expected? Output path validation of an action statement resulting in runtime exception Key: SPARK-4402 URL: https://issues.apache.org/jira/browse/SPARK-4402 Project: Spark Issue Type: Wish Reporter: Vijay Priority: Minor Output path validation is happening at the time of statement execution as a part of lazyevolution of action statement. But if the path already exists then it throws a runtime exception. Hence all the processing completed till that point is lost which results in resource wastage (processing time and CPU usage). If this I/O related validation is done before the RDD action operations then this runtime exception can be avoided. I believe similar validation/ feature is implemented in hadoop also. Example: SchemaRDD.saveAsTextFile() evaluated the path during runtime -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4402) Output path validation of an action statement resulting in runtime exception
[ https://issues.apache.org/jira/browse/SPARK-4402?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213739#comment-14213739 ] Sean Owen commented on SPARK-4402: -- Look at the code in PairRDDFunctions.saveAsHadoopDataset, which is what ultimately gets called. You'll see it try to check the output configuration upfront: {code} if (self.conf.getBoolean(spark.hadoop.validateOutputSpecs, true)) { // FileOutputFormat ignores the filesystem parameter val ignoredFs = FileSystem.get(hadoopConf) hadoopConf.getOutputFormat.checkOutputSpecs(ignoredFs, hadoopConf) } {code} It's enabled by default. I wonder if the code path is somehow using a nonstandard InputFormat that doesn't check? But this should cause an exception if the output path exists, before it starts, and was committed in SPARK-1100 for 1.0. Output path validation of an action statement resulting in runtime exception Key: SPARK-4402 URL: https://issues.apache.org/jira/browse/SPARK-4402 Project: Spark Issue Type: Wish Reporter: Vijay Priority: Minor Output path validation is happening at the time of statement execution as a part of lazyevolution of action statement. But if the path already exists then it throws a runtime exception. Hence all the processing completed till that point is lost which results in resource wastage (processing time and CPU usage). If this I/O related validation is done before the RDD action operations then this runtime exception can be avoided. I believe similar validation/ feature is implemented in hadoop also. Example: SchemaRDD.saveAsTextFile() evaluated the path during runtime -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4419) Upgrade Snappy Java to 1.1.1.6
[ https://issues.apache.org/jira/browse/SPARK-4419?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213744#comment-14213744 ] Apache Spark commented on SPARK-4419: - User 'JoshRosen' has created a pull request for this issue: https://github.com/apache/spark/pull/3287 Upgrade Snappy Java to 1.1.1.6 -- Key: SPARK-4419 URL: https://issues.apache.org/jira/browse/SPARK-4419 Project: Spark Issue Type: Improvement Components: Spark Core Reporter: Josh Rosen Priority: Minor We should upgrade the Snappy Java library to get better error reporting improvements. I had tried this previously in SPARK-4056 but had to revert that PR due to a memory leak / regression in Snappy Java. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-4430) Apache RAT Checks fail spuriously on test files
Ryan Williams created SPARK-4430: Summary: Apache RAT Checks fail spuriously on test files Key: SPARK-4430 URL: https://issues.apache.org/jira/browse/SPARK-4430 Project: Spark Issue Type: Bug Components: Build Reporter: Ryan Williams Several of my recent runs of {{./dev/run-tests}} have failed quickly due to Apache RAT checks, e.g.: {code} $ ./dev/run-tests = Running Apache RAT checks = Could not find Apache license headers in the following files: !? /Users/ryan/c/spark/streaming/FailureSuite/b732c105-4fd3-4330-ba6d-a366b340c303/test/28 !? /Users/ryan/c/spark/streaming/FailureSuite/b732c105-4fd3-4330-ba6d-a366b340c303/test/29 !? /Users/ryan/c/spark/streaming/FailureSuite/b732c105-4fd3-4330-ba6d-a366b340c303/test/30 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/10 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/11 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/12 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/13 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/14 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/15 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/16 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/17 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/18 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/19 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/20 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/21 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/22 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/23 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/24 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/25 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/26 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/27 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/28 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/29 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/30 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/7 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/8 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/9 [error] Got a return code of 1 on line 114 of the run-tests script. {code} I think it's fair to say that these are not useful errors for {{run-tests}} to crash on. Ideally we could tell the linter which files we care about having it lint and which we don't. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4430) Apache RAT Checks fail spuriously on test files
[ https://issues.apache.org/jira/browse/SPARK-4430?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213811#comment-14213811 ] Ryan Williams commented on SPARK-4430: -- I did find [this RAT JIRA|https://issues.apache.org/jira/browse/RAT-161] that seems somewhat related, but if there's anything we could do to work around this in Spark in the shorter term that would be great too. Apache RAT Checks fail spuriously on test files --- Key: SPARK-4430 URL: https://issues.apache.org/jira/browse/SPARK-4430 Project: Spark Issue Type: Bug Components: Build Reporter: Ryan Williams Several of my recent runs of {{./dev/run-tests}} have failed quickly due to Apache RAT checks, e.g.: {code} $ ./dev/run-tests = Running Apache RAT checks = Could not find Apache license headers in the following files: !? /Users/ryan/c/spark/streaming/FailureSuite/b732c105-4fd3-4330-ba6d-a366b340c303/test/28 !? /Users/ryan/c/spark/streaming/FailureSuite/b732c105-4fd3-4330-ba6d-a366b340c303/test/29 !? /Users/ryan/c/spark/streaming/FailureSuite/b732c105-4fd3-4330-ba6d-a366b340c303/test/30 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/10 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/11 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/12 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/13 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/14 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/15 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/16 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/17 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/18 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/19 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/20 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/21 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/22 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/23 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/24 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/25 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/26 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/27 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/28 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/29 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/30 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/7 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/8 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/9 [error] Got a return code of 1 on line 114 of the run-tests script. {code} I think it's fair to say that these are not useful errors for {{run-tests}} to crash on. Ideally we could tell the linter which files we care about having it lint and which we don't. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-4431) Implement efficient activeIterator for dense and sparse vector
DB Tsai created SPARK-4431: -- Summary: Implement efficient activeIterator for dense and sparse vector Key: SPARK-4431 URL: https://issues.apache.org/jira/browse/SPARK-4431 Project: Spark Issue Type: Improvement Components: MLlib Reporter: DB Tsai Previously, we were using Breeze's activeIterator to access the non-zero elements in sparse vector, and explicitly skipping the zero in dense/sparse vector using pattern matching. Due to the overhead, we switched back to native `while loop` in #SPARK-4129. However, #SPARK-4129 requires de-reference the dv.values/sv.values in each access to the value, and the zeros in dense vector and sparse vector if exist are skipped in the add function call; the overall penalty will be around 10% compared with de-reference once outside the while block, and checking if zero before calling the add function. The code is branched out for dense and sparse vector, and it's not easy to maintain in the long term. Not only this activeIterator implementation increases the performance, but the abstraction of accessing the non-zero elements in different vector type also helps the maintainability of codebase. In this PR, only MultivariateOnlineSummarizer uses new API as example, and others can be migrated to activeIterator later. Benchmarking with mnist8m dataset on single JVM with first 200 samples loaded in memory, and repeating 5000 times. Before change: Sparse Vector - 30.02 Dense Vector - 38.27 After this optimization: Sparse Vector - 27.54 Dense Vector - 35.13 -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4431) Implement efficient activeIterator for dense and sparse vector
[ https://issues.apache.org/jira/browse/SPARK-4431?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213826#comment-14213826 ] Apache Spark commented on SPARK-4431: - User 'dbtsai' has created a pull request for this issue: https://github.com/apache/spark/pull/3288 Implement efficient activeIterator for dense and sparse vector -- Key: SPARK-4431 URL: https://issues.apache.org/jira/browse/SPARK-4431 Project: Spark Issue Type: Improvement Components: MLlib Reporter: DB Tsai Previously, we were using Breeze's activeIterator to access the non-zero elements in sparse vector, and explicitly skipping the zero in dense/sparse vector using pattern matching. Due to the overhead, we switched back to native `while loop` in #SPARK-4129. However, #SPARK-4129 requires de-reference the dv.values/sv.values in each access to the value, and the zeros in dense vector and sparse vector if exist are skipped in the add function call; the overall penalty will be around 10% compared with de-reference once outside the while block, and checking if zero before calling the add function. The code is branched out for dense and sparse vector, and it's not easy to maintain in the long term. Not only this activeIterator implementation increases the performance, but the abstraction of accessing the non-zero elements in different vector type also helps the maintainability of codebase. In this PR, only MultivariateOnlineSummarizer uses new API as example, and others can be migrated to activeIterator later. Benchmarking with mnist8m dataset on single JVM with first 200 samples loaded in memory, and repeating 5000 times. Before change: Sparse Vector - 30.02 Dense Vector - 38.27 After this optimization: Sparse Vector - 27.54 Dense Vector - 35.13 -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Reopened] (SPARK-4404) SparkSubmitDriverBootstrapper should stop after its SparkSubmit sub-process ends
[ https://issues.apache.org/jira/browse/SPARK-4404?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Davies Liu reopened SPARK-4404: --- After this patch, the SparkSubmitDriverBootstrapper will not exit if SparkSubmit die first. SparkSubmitDriverBootstrapper should stop after its SparkSubmit sub-process ends - Key: SPARK-4404 URL: https://issues.apache.org/jira/browse/SPARK-4404 Project: Spark Issue Type: Bug Components: Spark Core Affects Versions: 1.1.0 Reporter: WangTaoTheTonic Assignee: WangTaoTheTonic Fix For: 1.2.0 When we have spark.driver.extra* or spark.driver.memory in SPARK_SUBMIT_PROPERTIES_FILE, spark-class will use SparkSubmitDriverBootstrapper to launch driver. If we get process id of SparkSubmitDriverBootstrapper and wanna kill it during its running, we expect its SparkSubmit sub-process stop also. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4404) SparkSubmitDriverBootstrapper should stop after its SparkSubmit sub-process ends
[ https://issues.apache.org/jira/browse/SPARK-4404?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213832#comment-14213832 ] Apache Spark commented on SPARK-4404: - User 'davies' has created a pull request for this issue: https://github.com/apache/spark/pull/3289 SparkSubmitDriverBootstrapper should stop after its SparkSubmit sub-process ends - Key: SPARK-4404 URL: https://issues.apache.org/jira/browse/SPARK-4404 Project: Spark Issue Type: Bug Components: Spark Core Affects Versions: 1.1.0 Reporter: WangTaoTheTonic Assignee: WangTaoTheTonic Fix For: 1.2.0 When we have spark.driver.extra* or spark.driver.memory in SPARK_SUBMIT_PROPERTIES_FILE, spark-class will use SparkSubmitDriverBootstrapper to launch driver. If we get process id of SparkSubmitDriverBootstrapper and wanna kill it during its running, we expect its SparkSubmit sub-process stop also. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-2335) k-Nearest Neighbor classification and regression for MLLib
[ https://issues.apache.org/jira/browse/SPARK-2335?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Brian Gawalt updated SPARK-2335: Shepherd: Ashutosh Trivedi k-Nearest Neighbor classification and regression for MLLib -- Key: SPARK-2335 URL: https://issues.apache.org/jira/browse/SPARK-2335 Project: Spark Issue Type: New Feature Components: MLlib Reporter: Brian Gawalt Priority: Minor Labels: features The k-Nearest Neighbor model for classification and regression problems is a simple and intuitive approach, offering a straightforward path to creating non-linear decision/estimation contours. It's downsides -- high variance (sensitivity to the known training data set) and computational intensity for estimating new point labels -- both play to Spark's big data strengths: lots of data mitigates data concerns; lots of workers mitigate computational latency. We should include kNN models as options in MLLib. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4404) SparkSubmitDriverBootstrapper should stop after its SparkSubmit sub-process ends
[ https://issues.apache.org/jira/browse/SPARK-4404?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213838#comment-14213838 ] Davies Liu commented on SPARK-4404: --- Also pyspark failed to start, if spark.driver.memory is set, I have not investigate the details yet. SparkSubmitDriverBootstrapper should stop after its SparkSubmit sub-process ends - Key: SPARK-4404 URL: https://issues.apache.org/jira/browse/SPARK-4404 Project: Spark Issue Type: Bug Components: Spark Core Affects Versions: 1.1.0 Reporter: WangTaoTheTonic Assignee: WangTaoTheTonic Fix For: 1.2.0 When we have spark.driver.extra* or spark.driver.memory in SPARK_SUBMIT_PROPERTIES_FILE, spark-class will use SparkSubmitDriverBootstrapper to launch driver. If we get process id of SparkSubmitDriverBootstrapper and wanna kill it during its running, we expect its SparkSubmit sub-process stop also. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4404) SparkSubmitDriverBootstrapper should stop after its SparkSubmit sub-process ends
[ https://issues.apache.org/jira/browse/SPARK-4404?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213840#comment-14213840 ] Marcelo Vanzin commented on SPARK-4404: --- Hmmm, my reading of the bug title and the bug description don't match. Title: SparkSubmitDriverBootstrapper should stop after SparkSubmit ends Descriptiont: killing SparkSubmitDriverBootstrapper should also kill SparkSubmit Pardon if I misunderstood something, but could you clarify what's not working as expected? SparkSubmitDriverBootstrapper should stop after its SparkSubmit sub-process ends - Key: SPARK-4404 URL: https://issues.apache.org/jira/browse/SPARK-4404 Project: Spark Issue Type: Bug Components: Spark Core Affects Versions: 1.1.0 Reporter: WangTaoTheTonic Assignee: WangTaoTheTonic Fix For: 1.2.0 When we have spark.driver.extra* or spark.driver.memory in SPARK_SUBMIT_PROPERTIES_FILE, spark-class will use SparkSubmitDriverBootstrapper to launch driver. If we get process id of SparkSubmitDriverBootstrapper and wanna kill it during its running, we expect its SparkSubmit sub-process stop also. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-4432) Resource(InStream) is not closed in TachyonStore
shimingfei created SPARK-4432: - Summary: Resource(InStream) is not closed in TachyonStore Key: SPARK-4432 URL: https://issues.apache.org/jira/browse/SPARK-4432 Project: Spark Issue Type: Bug Components: Block Manager Affects Versions: 1.1.0 Reporter: shimingfei In TachyonStore, InStream is not closed after data is read from Tachyon. which makes the blocks in Tachyon locked after accessed. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4432) Resource(InStream) is not closed in TachyonStore
[ https://issues.apache.org/jira/browse/SPARK-4432?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213845#comment-14213845 ] Apache Spark commented on SPARK-4432: - User 'shimingfei' has created a pull request for this issue: https://github.com/apache/spark/pull/3290 Resource(InStream) is not closed in TachyonStore Key: SPARK-4432 URL: https://issues.apache.org/jira/browse/SPARK-4432 Project: Spark Issue Type: Bug Components: Block Manager Affects Versions: 1.1.0 Reporter: shimingfei In TachyonStore, InStream is not closed after data is read from Tachyon. which makes the blocks in Tachyon locked after accessed. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-4433) Racing condition in zipWithIndex
Xiangrui Meng created SPARK-4433: Summary: Racing condition in zipWithIndex Key: SPARK-4433 URL: https://issues.apache.org/jira/browse/SPARK-4433 Project: Spark Issue Type: Bug Components: Spark Core Affects Versions: 1.0.2, 1.1.1, 1.2.0 Reporter: Xiangrui Meng Assignee: Xiangrui Meng Spark hangs with the following code: {code} sc.parallelize(1 to 10).zipWithIndex.repartition(10).count() {code} This is because ZippedWithIndexRDD triggers a job in getPartitions and it cause a deadlock in DAGScheduler.getPreferredLocs. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-2335) k-Nearest Neighbor classification and regression for MLLib
[ https://issues.apache.org/jira/browse/SPARK-2335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213849#comment-14213849 ] Kaushik Ranjan commented on SPARK-2335: --- Ha ha. Shepherd and I were working on this together. [~bgawalt] - if you could review the code and suggest changes(if any), I can take it forward k-Nearest Neighbor classification and regression for MLLib -- Key: SPARK-2335 URL: https://issues.apache.org/jira/browse/SPARK-2335 Project: Spark Issue Type: New Feature Components: MLlib Reporter: Brian Gawalt Priority: Minor Labels: features The k-Nearest Neighbor model for classification and regression problems is a simple and intuitive approach, offering a straightforward path to creating non-linear decision/estimation contours. It's downsides -- high variance (sensitivity to the known training data set) and computational intensity for estimating new point labels -- both play to Spark's big data strengths: lots of data mitigates data concerns; lots of workers mitigate computational latency. We should include kNN models as options in MLLib. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4433) Racing condition in zipWithIndex
[ https://issues.apache.org/jira/browse/SPARK-4433?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213850#comment-14213850 ] Apache Spark commented on SPARK-4433: - User 'mengxr' has created a pull request for this issue: https://github.com/apache/spark/pull/3291 Racing condition in zipWithIndex Key: SPARK-4433 URL: https://issues.apache.org/jira/browse/SPARK-4433 Project: Spark Issue Type: Bug Components: Spark Core Affects Versions: 1.0.2, 1.1.1, 1.2.0 Reporter: Xiangrui Meng Assignee: Xiangrui Meng Spark hangs with the following code: {code} sc.parallelize(1 to 10).zipWithIndex.repartition(10).count() {code} This is because ZippedWithIndexRDD triggers a job in getPartitions and it cause a deadlock in DAGScheduler.getPreferredLocs. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4404) SparkSubmitDriverBootstrapper should stop after its SparkSubmit sub-process ends
[ https://issues.apache.org/jira/browse/SPARK-4404?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213852#comment-14213852 ] Davies Liu commented on SPARK-4404: --- This JIRA is re-opened, the new bug is introduced by this JIRA. Should I create a new JIRA for it? SparkSubmitDriverBootstrapper should stop after its SparkSubmit sub-process ends - Key: SPARK-4404 URL: https://issues.apache.org/jira/browse/SPARK-4404 Project: Spark Issue Type: Bug Components: Spark Core Affects Versions: 1.1.0 Reporter: WangTaoTheTonic Assignee: WangTaoTheTonic Fix For: 1.2.0 When we have spark.driver.extra* or spark.driver.memory in SPARK_SUBMIT_PROPERTIES_FILE, spark-class will use SparkSubmitDriverBootstrapper to launch driver. If we get process id of SparkSubmitDriverBootstrapper and wanna kill it during its running, we expect its SparkSubmit sub-process stop also. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Resolved] (SPARK-4419) Upgrade Snappy Java to 1.1.1.6
[ https://issues.apache.org/jira/browse/SPARK-4419?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Reynold Xin resolved SPARK-4419. Resolution: Fixed Fix Version/s: 1.2.0 Assignee: Josh Rosen Upgrade Snappy Java to 1.1.1.6 -- Key: SPARK-4419 URL: https://issues.apache.org/jira/browse/SPARK-4419 Project: Spark Issue Type: Improvement Components: Spark Core Reporter: Josh Rosen Assignee: Josh Rosen Priority: Minor Fix For: 1.2.0 We should upgrade the Snappy Java library to get better error reporting improvements. I had tried this previously in SPARK-4056 but had to revert that PR due to a memory leak / regression in Snappy Java. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Closed] (SPARK-4427) In Spark Streaming when we perform window operations , it wil caluclate based on system time, i need to override it, i mean instead of getting current time app need to g
[ https://issues.apache.org/jira/browse/SPARK-4427?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Reynold Xin closed SPARK-4427. -- In Spark Streaming when we perform window operations , it wil caluclate based on system time, i need to override it, i mean instead of getting current time app need to get from my text file. Key: SPARK-4427 URL: https://issues.apache.org/jira/browse/SPARK-4427 Project: Spark Issue Type: Bug Reporter: ch.prasad Original Estimate: 24h Remaining Estimate: 24h Please provide solution asap. in window operation wen we give window size, it get data from rdd's by caluclating window size with current time , i need to change current time , to be read from my file. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-4426) The symbol of BitwiseOr is wrong, should not be ''
[ https://issues.apache.org/jira/browse/SPARK-4426?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Reynold Xin updated SPARK-4426: --- Target Version/s: 1.2.0 (was: 1.2.0, 1.3.0) The symbol of BitwiseOr is wrong, should not be '' --- Key: SPARK-4426 URL: https://issues.apache.org/jira/browse/SPARK-4426 Project: Spark Issue Type: Bug Components: SQL Affects Versions: 1.3.0 Reporter: Kousuke Saruta Assignee: Kousuke Saruta Priority: Minor Fix For: 1.2.0 The symbol of BitwiseOr is defined as '' but I think it's wrong. It should be '|'. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Resolved] (SPARK-4426) The symbol of BitwiseOr is wrong, should not be ''
[ https://issues.apache.org/jira/browse/SPARK-4426?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Reynold Xin resolved SPARK-4426. Resolution: Fixed Fix Version/s: 1.2.0 Assignee: Kousuke Saruta The symbol of BitwiseOr is wrong, should not be '' --- Key: SPARK-4426 URL: https://issues.apache.org/jira/browse/SPARK-4426 Project: Spark Issue Type: Bug Components: SQL Affects Versions: 1.3.0 Reporter: Kousuke Saruta Assignee: Kousuke Saruta Priority: Minor Fix For: 1.2.0 The symbol of BitwiseOr is defined as '' but I think it's wrong. It should be '|'. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-4430) Apache RAT Checks fail spuriously on test files
[ https://issues.apache.org/jira/browse/SPARK-4430?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14213873#comment-14213873 ] Sean Owen commented on SPARK-4430: -- I imagine the real issue is that the test should clean up these files if it does not already. Those aren't in the source tree. It is not really a RAT config issue. If the files were left because tests crashed or were killed then just delete them. Apache RAT Checks fail spuriously on test files --- Key: SPARK-4430 URL: https://issues.apache.org/jira/browse/SPARK-4430 Project: Spark Issue Type: Bug Components: Build Reporter: Ryan Williams Several of my recent runs of {{./dev/run-tests}} have failed quickly due to Apache RAT checks, e.g.: {code} $ ./dev/run-tests = Running Apache RAT checks = Could not find Apache license headers in the following files: !? /Users/ryan/c/spark/streaming/FailureSuite/b732c105-4fd3-4330-ba6d-a366b340c303/test/28 !? /Users/ryan/c/spark/streaming/FailureSuite/b732c105-4fd3-4330-ba6d-a366b340c303/test/29 !? /Users/ryan/c/spark/streaming/FailureSuite/b732c105-4fd3-4330-ba6d-a366b340c303/test/30 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/10 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/11 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/12 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/13 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/14 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/15 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/16 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/17 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/18 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/19 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/20 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/21 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/22 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/23 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/24 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/25 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/26 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/27 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/28 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/29 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/30 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/7 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/8 !? /Users/ryan/c/spark/streaming/FailureSuite/b98beebe-98b0-472a-b4a5-060bcd91e401/test/9 [error] Got a return code of 1 on line 114 of the run-tests script. {code} I think it's fair to say that these are not useful errors for {{run-tests}} to crash on. Ideally we could tell the linter which files we care about having it lint and which we don't. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org