SparkSQL中的三种Join及其实现(broadcast join、shuffle hash join和sort merge join) 1.小表对大表(broadcast join) 将小表的数据分发到每个节点上,供大表使用。executor存储小表的全部数据,一定程度上牺牲了空间,换取shuffle操作大量的耗时,这在SparkSQL中称作Broadcast Join
Broadcast Hash Join(BHJ)是SparkSQL 实现分布式join的四种核心方式之一,另外三个是 Sort Merge Join(SMJ) 、 Shuffled Hash Join(SHJ)、Broadcast nested loop join (BNLJ)。 可以通过在SQL中添加hint的方式指定采用BHJ实现join(参考[SparkSQL tunning](Performance Tuning))。但是,更多的情况是依赖SparkSQL框架自动...
Spark在判断能否转为BroadCastJoin时主要是根据输入表的大小是否超过了 spark.sql.autoBroadcastJoinThreshold 参数所配置的大小,如果未超过阈值则可以转为BroadCastJoin. 结论 先说下整个判断的流程: 1.首先在非分区表情况下并且 spark.sql.statistics.fallBackToHdfs此参数开启时会统计表hdfs目录大小 2.在物理计划生成...
spark.sql.shuffle.partitions 200 配置数据混洗(shuffle)时(join或者聚合操作),使用的分区数 4. sparkSql参数调优 A. Spark.sql.codegen 默认false 若设置为true,Spark SQL会将每个查询都编译为Java字节码。当查询量较大时,这样的设置能够改进查询性能,但不适用于查询量小的情形. B. spark.sql.inMemoryColumnar...
res2: org.apache.spark.sql.execution.SparkPlan = *(1) BroadcastHashJoin [id1#3], [id2#8], Inner, BuildRight :- LocalTableScan [id1#3] +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint))) ...
#Enable broadcast Join and#Set Threshold limit of size in bytes of a DataFrame to broadcastspark.conf.set("spark.sql.autoBroadcastJoinThreshold",104857600)#Disable broadcast Joinspark.conf.set("spark.sql.autoBroadcastJoinThreshold",-1) The threshold value for broadcast DataFrame is passed in bytes...
***在mysql命令行下执行sql文件*** C:\Windows\system32>cd E:\MySQL\mysql-5.7.16-winx64\bin...
testTable3= testTable1.join(broadcast(testTable2), Seq("id"), "right_outer") 3)自动优化 org.apache.spark.sql.execution.SparkStrategies.JoinSelection privatedef canBroadcast(plan: LogicalPlan): Boolean ={ plan.statistics.isBroadcastable||(plan.statistics.sizeInBytes>= 0 &&plan.statistics.sizeIn...
BroadcastHashJoin示例: package com.dx.testbroadcast; import org.apache.spark.SparkConf; import org.apache.spark.sql.Dataset; import org.apache.spark.sql.Row; import org.apache.spark.sql.SparkSession; import org.apache.spark.sql.functions; ...
The mechanism of broadcast in Spark is to collect the result of an RDD and then broadcast it. This introduces some extra latency. We can broadcast the RDD directly from executors. This patch implements broadcast from executors, and applies it on broadcast join of Spark SQL. ...