You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@iceberg.apache.org by GitBox <gi...@apache.org> on 2021/04/21 16:52:53 UTC
[GitHub] [iceberg] mayursrivastava edited a comment on pull request #2286: Add Arrow vectorized reader
mayursrivastava edited a comment on pull request #2286:
URL: https://github.com/apache/iceberg/pull/2286#issuecomment-824210180
>./gradlew :iceberg-spark:jmh -PjmhIncludeRegex=VectorizedReadFlatParquetDataBenchmark -PjmhOutputPath=benchmark/results.txt
@rymurr, is this :iceberg-spark2:jmh? Looks like this requires Java8 runtime. Am I right? I ran it on the master branch (without my changes), but it fails with the following error. Does it need a powerful machine?
# JMH version: 1.21
# VM version: JDK 1.8.0_282, OpenJDK 64-Bit Server VM, 25.282-b08
# VM invoker: /usr/lib/jvm/java-8-openjdk-amd64/jre/bin/java
# VM options: <none>
# Warmup: 3 iterations, single-shot each
# Measurement: 5 iterations, single-shot each
# Timeout: 10 min per iteration
# Threads: 1 thread
# Benchmark mode: Single shot invocation time
# Benchmark: org.apache.iceberg.spark.source.parquet.vectorized.VectorizedReadDictionaryEncodedFlatParquetDataBenchmark.readDatesIcebergVectorized5k
# Run progress: 0.00% complete, ETA 00:00:00
# Fork: 1 of 1
# Warmup Iteration 1: (*interrupt*) <failure>
java.lang.InterruptedException
at java.util.concurrent.locks.AbstractQueuedSynchronizer.doAcquireSharedInterruptibly(AbstractQueuedSynchronizer.java:998)
at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireSharedInterruptibly(AbstractQueuedSynchronizer.java:1304)
at scala.concurrent.impl.Promise$DefaultPromise.tryAwait(Promise.scala:206)
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:222)
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:157)
at org.apache.spark.util.ThreadUtils$.awaitReady(ThreadUtils.scala:243)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:750)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec.doExecute(WriteToDataSourceV2Exec.scala:64)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:83)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:81)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:696)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:696)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:80)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:127)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:75)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:696)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:280)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:249)
at org.apache.iceberg.spark.source.IcebergSourceBenchmark.appendAsFile(IcebergSourceBenchmark.java:130)
at org.apache.iceberg.spark.source.parquet.vectorized.VectorizedReadDictionaryEncodedFlatParquetDataBenchmark.appendData(VectorizedReadDictionaryEncodedFlatParquetDataBenchmark.java:82)
at org.apache.iceberg.spark.source.parquet.vectorized.VectorizedReadDictionaryEncodedFlatParquetDataBenchmark.setupBenchmark(VectorizedReadDictionaryEncodedFlatParquetDataBenchmark.java:56)
at org.apache.iceberg.spark.source.parquet.vectorized.generated.VectorizedReadDictionaryEncodedFlatParquetDataBenchmark_readDatesIcebergVectorized5k_jmhTest._jmh_tryInit_f_vectorizedreaddictionaryencodedflatparquetdatabenchmark0_G(VectorizedReadDictionaryEncodedFlatParquetDataBenchmark_readDatesIcebergVectorized5k_jmhTest.java:438)
at org.apache.iceberg.spark.source.parquet.vectorized.generated.VectorizedReadDictionaryEncodedFlatParquetDataBenchmark_readDatesIcebergVectorized5k_jmhTest.readDatesIcebergVectorized5k_SingleShotTime(VectorizedReadDictionaryEncodedFlatParquetDataBenchmark_readDatesIcebergVectorized5k_jmhTest.java:363)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.openjdk.jmh.runner.BenchmarkHandler$BenchmarkTask.call(BenchmarkHandler.java:453)
at org.openjdk.jmh.runner.BenchmarkHandler$BenchmarkTask.call(BenchmarkHandler.java:437)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Benchmark had encountered error, and fail on error was requested
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@iceberg.apache.org
For additional commands, e-mail: issues-help@iceberg.apache.org