Add Spark Job Launcher tool #9288
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## master #9288 +/- ##
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KKcorps
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| <groupId>org.apache.spark</groupId> | ||
| <artifactId>spark-launcher_${scala.version}</artifactId> | ||
| <version>${spark.version}</version> | ||
| <exclusions> |
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I do have some minor concerns about adding dependencies on Spark here. But since it's only pinot-tools, it's not so important.
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This dep is pretty basic. Only contains couple of classes and one more dependency. So including it isn't a main concern. Earlier I had included spark-core which was a major one and could have caused a lot of issues.
| @@ -34,6 +34,8 @@ | |||
| <properties> | |||
| <pinot.root>${basedir}/..</pinot.root> | |||
| <aws.version>2.14.28</aws.version> | |||
| <scala.version>2.12</scala.version> | |||
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Once you start pulling in Scala code, you need to ensure that every dependency that's also using Scala is using the same version. So I think this should go in the top-level pom.xml file. Also note that pinot-kafka and pinot-spark have dependencies on Scala 2.11, which I believe will cause runtime problems if they are on the classpath when the tool is being run (and it's using 2.12).
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I have actually excluded the scala code from plugin. It is just that the plugin requires it in name.
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It is failing in some cases like local environment but multi threaded. Working on fixing those post which we can merge. |
| // Kafka plugins need to be excluded as they contain scala dependencies which cause | ||
| // NoSuchMethodErrors with runtime spark. | ||
| // It is also fine to exclude Kafka plugins as they are not going to be used in batch ingestion in any case | ||
| @CommandLine.Option(names = {"-pluginsToExclude"}, defaultValue = "pinot-kafka-0.9:pinot-kafka-2.0", required = |
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i wonder if we already have a property file and a jobspec file. do we still want to support these commandline options
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Yes, that can be done as well. My initial thought process when writing this was to not use ingestion spec at all in the command code and only use it inside the spark job. Reason being it puts the limitation of always providing ingestion spec as a local file path and not S3.
However, I did ended up using the spec because otherwise we can't load the PinotFS classes and find appropriate plugin jars in S3, GCS etc.
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I will take this up as a seperate PR
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The users currently need to create the whole spark-submit command to run a spark job for batch ingestion. With so many plugins available inside pinot leads a lot of classpath errors and you also need to take care of various arguments based on the environment in which you are running. This new command in
pinot-adminaims to simply this for the users.Example
Previously if you had to run
export PINOT_VERSION=0.11.0-SNAPSHOT export PINOT_DISTRIBUTION_DIR=/Users/kharekartik/Documents/Developer/pinot/build/ spark-submit --class org.apache.pinot.tools.admin.command.LaunchDataIngestionJobCommand --master yarn --deploy-mode client --jars ${PINOT_DISTRIBUTION_DIR}/lib/pinot-all-0.11.0-SNAPSHOT-jar-with-dependencies.jar,${PINOT_DISTRIBUTION_DIR}/plugins/pinot-input-format/pinot-parquet/pinot-parquet-0.11.0-SNAPSHOT-shaded.jar,${PINOT_DISTRIBUTION_DIR}/plugins/pinot-file-system/pinot-s3/pinot-s3-0.11.0-SNAPSHOT-shaded.jar,${PINOT_DISTRIBUTION_DIR}/plugins-external/pinot-batch-ingestion/pinot-batch-ingestion-spark-3.2/pinot-batch-ingestion-spark-3.2-0.11.0-SNAPSHOT-shaded.jar local://${PINOT_DISTRIBUTION_DIR}/lib/pinot-all-0.11.0-SNAPSHOT-jar-with-dependencies.jar -jobSpecFile parquet_ingestion_spec_spark3_students.ymlbut now you can now use
export SPARK_HOME=/usr/lib/spark/ bin/pinot-admin.sh LaunchSparkDataIngestionJob -jobSpecFile parquet_ingestion_spec_spark3_students.yml -pluginsToLoad pinot-parquet:pinot-s3 -master yarnAdditional Options
You can also mention any additional spark configurations using the
-sparkConfoption-sparkConf spark.executor.cores=3:num-executors=4Users can also specify jars directly from S3/GCS instead of local disk for environments like EMR
-pinotBaseDir s3://your-bucket/apache-pinot-0.11.0-SNAPSHOTYou can choose whether to run spark 2.x or 3.x with the following option (default is SPARK_3)
-sparkVersion SPARK_2