/Firestorm

Firestorm is a Remote Shuffle Service, and provides the capability for Apache Spark and Apache Hadoop MapReduce applications to store shuffle data on remote servers

Primary LanguageJavaOtherNOASSERTION

What is Firestorm

Firestorm is a Remote Shuffle Service, and provides the capability for Apache Spark applications to store shuffle data on remote servers.

Architecture

Rss Architecture Firestorm contains coordinator cluster, shuffle server cluster and remote storage(eg, HDFS) if necessary.

Coordinator will collect status of shuffle server and do the assignment for the job.

Shuffle server will receive the shuffle data, merge them and write to storage.

Depend on different situation, Firestorm supports Memory & Local, Memory & Remote Storage(eg, HDFS), Memory & Local & Remote Storage(recommendation for production environment).

Shuffle Process with Firestorm

  • Spark driver ask coordinator to get shuffle server for shuffle process

  • Spark task write shuffle data to shuffle server with following step: Rss Shuffle_Write

    1. Send KV data to buffer
    2. Flush buffer to queue when buffer is full or buffer manager is full
    3. Thread pool get data from queue
    4. Request memory from shuffle server first and send the shuffle data
    5. Shuffle server cache data in memory first and flush to queue when buffer manager is full
    6. Thread pool get data from queue
    7. Write data to storage with index file and data file
    8. After write data, task report all blockId to shuffle server, this step is used for data validation later
    9. Store taskAttemptId in MapStatus to support Spark speculation

  • Depend on different storage type, spark task read shuffle data from shuffle server or remote storage or both of them.

Shuffle file format

The shuffle data is stored with index file and data file. Data file has all blocks for specific partition and index file has metadata for every block.

Rss Shuffle_Write

Supported Spark Version

Current support Spark 2.3.x, Spark 2.4.x, Spark3.0.x, Spark 3.1.x, Spark 3.2.x

Note: To support dynamic allocation, the patch(which is included in client-spark/patch folder) should be applied to Spark

Supported MapReduce Version

Current support Hadoop 2.8.5's MapReduce framework.

Building Firestorm

Firestorm is built using Apache Maven. To build it, run:

mvn -DskipTests clean package

To package the Firestorm, run:

./build_distribution.sh

rss-xxx.tgz will be generated for deployment

Deploy

Deploy Coordinator

  1. unzip package to RSS_HOME
  2. update RSS_HOME/bin/rss-env.sh, eg, 
      JAVA_HOME=<java_home>
  HADOOP_HOME=<hadoop home>
  XMX_SIZE="16g"
  3. update RSS_HOME/conf/coordinator.conf, eg, 
      rss.rpc.server.port 19999
  rss.jetty.http.port 19998
  rss.coordinator.server.heartbeat.timeout 30000
  rss.coordinator.app.expired 60000
  rss.coordinator.shuffle.nodes.max 5
  # enable dynamicClientConf, and coordinator will be responsible for most of client conf
  rss.coordinator.dynamicClientConf.enabled true
  # config the path of client conf
  rss.coordinator.dynamicClientConf.path <RSS_HOME>/conf/dynamic_client.conf
  # config the path of excluded shuffle server
  rss.coordinator.exclude.nodes.file.path <RSS_HOME>/conf/exclude_nodes
  4. update <RSS_HOME>/conf/dynamic_client.conf, rss client will get default conf from coordinator eg, 
     # MEMORY_LOCALFILE_HDFS is recommandation for production environment
 rss.storage.type MEMORY_LOCALFILE_HDFS
 # multiple remote storages are supported, and client will get assignment from coordinator
 rss.coordinator.remote.storage.path hdfs://cluster1/path,hdfs://cluster2/path
 rss.writer.require.memory.retryMax 1200
 rss.client.retry.max 100
 rss.writer.send.check.timeout 600000
 rss.client.read.buffer.size 14m
  5. start Coordinator 
     bash RSS_HOME/bin/start-coordnator.sh

Deploy Shuffle Server

  1. unzip package to RSS_HOME
  2. update RSS_HOME/bin/rss-env.sh, eg, 
      JAVA_HOME=<java_home>
  HADOOP_HOME=<hadoop home>
  XMX_SIZE="80g"
  3. update RSS_HOME/conf/server.conf, eg, 
      rss.rpc.server.port 19999
  rss.jetty.http.port 19998
  rss.rpc.executor.size 2000
  # it should be configed the same as in coordinator
  rss.storage.type MEMORY_LOCALFILE_HDFS
  rss.coordinator.quorum <coordinatorIp1>:19999,<coordinatorIp2>:19999
  # local storage path for shuffle server
  rss.storage.basePath /data1/rssdata,/data2/rssdata....
  # it's better to config thread num according to local disk num
  rss.server.flush.thread.alive 5
  rss.server.flush.threadPool.size 10
  rss.server.buffer.capacity 40g
  rss.server.read.buffer.capacity 20g
  rss.server.heartbeat.timeout 60000
  rss.server.heartbeat.interval 10000
  rss.rpc.message.max.size 1073741824
  rss.server.preAllocation.expired 120000
  rss.server.commit.timeout 600000
  rss.server.app.expired.withoutHeartbeat 120000
  # note: the default value of rss.server.flush.cold.storage.threshold.size is 64m
  # there will be no data written to DFS if set it as 100g even rss.storage.type=MEMORY_LOCALFILE_HDFS
  # please set proper value if DFS is used, eg, 64m, 128m.
  rss.server.flush.cold.storage.threshold.size 100g
  4. start Shuffle Server 
     bash RSS_HOME/bin/start-shuffle-server.sh

Deploy Spark Client

  1. Add client jar to Spark classpath, eg, SPARK_HOME/jars/

    The jar for Spark2 is located in <RSS_HOME>/jars/client/spark2/rss-client-XXXXX-shaded.jar

    The jar for Spark3 is located in <RSS_HOME>/jars/client/spark3/rss-client-XXXXX-shaded.jar

  2. Update Spark conf to enable Firestorm, eg,

    spark.shuffle.manager org.apache.spark.shuffle.RssShuffleManager
spark.rss.coordinator.quorum <coordinatorIp1>:19999,<coordinatorIp2>:19999

Support Spark dynamic allocation

To support spark dynamic allocation with Firestorm, spark code should be updated. There are 2 patches for spark-2.4.6 and spark-3.1.2 in spark-patches folder for reference.

After apply the patch and rebuild spark, add following configuration in spark conf to enable dynamic allocation:

spark.shuffle.service.enabled false
spark.dynamicAllocation.enabled true

Deploy MapReduce Client

  1. Add client jar to the classpath of each NodeManager, e.g., /share/hadoop/mapreduce/

The jar for MapReduce is located in <RSS_HOME>/jars/client/mr/rss-client-mr-XXXXX-shaded.jar

  1. Update MapReduce conf to enable Firestorm, eg,

    -Dmapreduce.rss.coordinator.quorum=<coordinatorIp1>:19999,<coordinatorIp2>:19999
-Dyarn.app.mapreduce.am.command-opts=org.apache.hadoop.mapreduce.v2.app.RssMRAppMaster
-Dmapreduce.job.map.output.collector.class=org.apache.hadoop.mapred.RssMapOutputCollector
-Dmapreduce.job.reduce.shuffle.consumer.plugin.class=org.apache.hadoop.mapreduce.task.reduce.RssShuffle

Note that the RssMRAppMaster will automatically disable slow start (i.e., mapreduce.job.reduce.slowstart.completedmaps=1) and job recovery (i.e., yarn.app.mapreduce.am.job.recovery.enable=false)

Configuration

The important configuration is listed as following.

Coordinator

Property Name Default Description
rss.coordinator.server.heartbeat.timeout 30000 Timeout if can't get heartbeat from shuffle server
rss.coordinator.assignment.strategy PARTITION_BALANCE Strategy for assigning shuffle server, PARTITION_BALANCE should be used for workload balance
rss.coordinator.app.expired 60000 Application expired time (ms), the heartbeat interval should be less than it
rss.coordinator.shuffle.nodes.max 9 The max number of shuffle server when do the assignment
rss.coordinator.dynamicClientConf.path - The path of configuration file which have default conf for rss client
rss.coordinator.exclude.nodes.file.path - The path of configuration file which have exclude nodes
rss.coordinator.exclude.nodes.check.interval.ms 60000 Update interval (ms) for exclude nodes
rss.rpc.server.port - RPC port for coordinator
rss.jetty.http.port - Http port for coordinator

Shuffle Server

Property Name Default Description
rss.coordinator.quorum - Coordinator quorum
rss.rpc.server.port - RPC port for Shuffle server
rss.jetty.http.port - Http port for Shuffle server
rss.server.buffer.capacity - Max memory of buffer manager for shuffle server
rss.server.memory.shuffle.highWaterMark.percentage 75.0 Threshold of spill data to storage, percentage of rss.server.buffer.capacity
rss.server.memory.shuffle.lowWaterMark.percentage 25.0 Threshold of keep data in memory, percentage of rss.server.buffer.capacity
rss.server.read.buffer.capacity - Max size of buffer for reading data
rss.server.heartbeat.interval 10000 Heartbeat interval to Coordinator (ms)
rss.server.flush.threadPool.size 10 Thread pool for flush data to file
rss.server.commit.timeout 600000 Timeout when commit shuffle data (ms)
rss.storage.type - Supports MEMORY_LOCALFILE, MEMORY_HDFS, MEMORY_LOCALFILE_HDFS
rss.server.flush.cold.storage.threshold.size 64M The threshold of data size for LOACALFILE and HDFS if MEMORY_LOCALFILE_HDFS is used

Spark Client

Property Name Default Description
spark.rss.writer.buffer.size 3m Buffer size for single partition data
spark.rss.writer.buffer.spill.size 128m Buffer size for total partition data
spark.rss.coordinator.quorum - Coordinator quorum
spark.rss.storage.type - Supports MEMORY_LOCALFILE, MEMORY_HDFS, MEMORY_LOCALFILE_HDFS
spark.rss.client.send.size.limit 16m The max data size sent to shuffle server
spark.rss.client.read.buffer.size 32m The max data size read from storage
spark.rss.client.send.threadPool.size 10 The thread size for send shuffle data to shuffle server

MapReduce Client

Property Name Default Description
mapreduce.rss.coordinator.quorum - Coordinator quorum
mapreduce.rss.storage.type - Supports MEMORY_LOCALFILE, MEMORY_HDFS, MEMORY_LOCALFILE_HDFS
mapreduce.rss.client.max.buffer.size 3k The max buffer size in map side
mapreduce.rss.client.read.buffer.size 32m The max data size read from storage

LICENSE

Firestorm is under the Apache License Version 2.0. See the LICENSE file for details.

Contributing

For more information about contributing issues or pull requests, see Firestorm Contributing Guide.

Support

We provide free support for users using this project. If you want to join user wechat group for further help and collaboration. You can scan the following QR code or search wechatID xinghuojihua_01, add our assistant on wechat, and remark Firestorm. The assistant will help you join our wechat group.

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