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Apache Kylin

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Apache Kylin : Analytical Data Warehouse for Big Data

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Spark resources automatic adjustment strategy (experimental feature)


PropertyDefaultDescriptionSince

kylin.spark-conf.auto.prior

trueFor a CubeBuildJob and CubeMergeJob, it is important to allocate enough and proper resources(cpu/memory), including following config entries mainly:
  • spark.driver.memory
  • spark.executor.memory
  • spark.executor.cores
  • spark.executor.memoryOverhead
  • spark.executor.instances
  • spark.sql.shuffle.partitions

When `kylin.spark-conf.auto.prior` is set to true, Kylin will try to adjust above config entries according to:
  • Count of cuboids to be built
  • Max size of fact table
  • Available resources from current resource manager 's queue

But user still can choose to override some config via in the form of `kylin.engine.spark-conf.` in <key> = <value>` at the Cube level. The parameter value configured by the user will overwrite the parameter value of automatic parameter adjustment.
Check detail at How to improve cube building and query performance		4.0.0

kylin.engine.spark-conf.spark.master

yarnThe cluster manager to connect to. Kylin support set it to yarn/local/standalone.

kylin.engine.spark-conf.spark.submit.deployMode

client

The deploy mode of Spark driver program, either "client" or "cluster", Which means to launch driver program locally ("client") or remotely ("cluster") on one of the nodes inside the cluster.


kylin.engine.spark-conf.spark.yarn.queue

default

kylin.engine.spark-conf.spark.shuffle.service.enabled

false

Enables the external shuffle service. This service preserves the shuffle files written by executors so the executors can be safely removed. The external shuffle service must be set up in order to enable it.


4.0.0
kylin.engine.spark-conf.spark.eventLog.enabledtrueWhether to log Spark events, useful for reconstructing the Web UI after the application has finished.

kylin.engine.spark-conf.spark.eventLog.dir

hdfs\:///kylin/spark-history

Base directory in which Spark events are logged, if spark.eventLog.enabled is true. 

kylin.engine.spark-conf.spark.hadoop.yarn.timeline-service.enabled

false

kylin.engine.spark-conf.spark.executor.extraJavaOptions


Code Block
languagebash
titleextraJavaOptions
collapsetrue
-Dfile.encoding=UTF-8 
-Dhdp.version=current 
-Dlog4j.configuration=spark-executor-log4j.properties 
-Dlog4j.debug 
-Dkylin.hdfs.working.dir=${hdfs.working.dir} 
-Dkylin.metadata.identifier=${kylin.metadata.url.identifier} -Dkylin.spark.category=job 
-Dkylin.spark.project=${job.project} 
-Dkylin.spark.identifier=${job.id} 
-Dkylin.spark.jobName=${job.stepId} 
-Duser.timezone=${user.timezone}




kylin.engine.spark-conf.spark.yarn.jars

hdfs://localhost:9000/spark2_jars/*

Manually upload spark-assembly jar to HDFS and then set this property will avoid repeatedly uploading jar at runtime

nullUser can choose to set spark conf of Cube/Merge Job at Cube level.4.0.0


kylin.engine.driver-memory-base
1024

Driver memory(spark.driver.memory) is auto adjusted by cuboid count and configuration.

kylin.engine.driver-memory-strategy will decided some level. For example, "2,20,100" will transfer to four cuboid count ranges, from low to high, as following: 

  • Level 1 : (0, 2)
  • Level 2 : (2, 20)
  • Level 3 : (20, 100)
  • Level 4 : (100, +)

So, we can find a proper level for specific cuboid count. 12 will be level 2, and 230 will be level 4.

Driver memory will be calculated by following formula : 

Code Block
languagesql
themeEmacs
min(kylin.engine.driver-memory-base * level, kylin.engine.driver-memory-maximum)


4.0.0
kylin.engine.driver-memory-maximum
4096See above.4.0.0
kylin.engine.driver-memory-strategy
2,20,100See above.4.0.0
kylin.engine.base-executor-instance
5
4.0.0
kylin.engine.spark.required-cores
1
4.0.0
kylin.engine.executor-instance-strategy
100,2,500,3,1000,4
4.0.0
kylin.engine.retry-memory-gradient


4.0.0

...

Following files are under WORKING-DIR/$PROJECT/job_tmp/${JOB_ID}/share, produced in the first step of BuildJob.  And they served to spark resources automatic adjustment strategy. (Source code : ResourceDetectBeforeCubingJob).

Resource Detect FileData TypeFormatDescription
count_distinct.jsonBooleanBinary

Cube contains COUNT_DISTINCT(bitmap) measure.

Sample :

true

${JOB_ID}_resource_path.json

Map<String, List<String>>

Binary

Key is cuboid ID, and value is cuboid's parent dataset's partition path.

-1 means Flat Table.

Sample :

Code Block
languagejs
themeDJango
{
   "-1" : ["hdfs://cdh-master:8020/user/hive/warehouse/tpch_flat_orc_10.db/lineitem", 
"hdfs://cdh-master:8020/user/hive/warehouse/tpch_flat_orc_10.db/part"]
}


${JOB_ID}_cubing_detect_items.jsonMap<String, Integer>Binary

Key is cuboid ID, and value is cuboid's parent dataset's partition count.

Sample : 

Code Block
languagejs
themeDJango
{
  "-1": 32
}



Global dictionary

PropertyDefaultDescriptionSince
















kylin.dictionary.detect-data-skew-sample-enabled



kylin.dictionary.detect-data-skew-sample-rate



kylin.dictionary.detect-data-skew-percentage-threshold



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