spark.sql.shuffle.partitions configures the number of partitions that are used when shuffling data for joins or aggregations. spark.default.parallelism is the default number of partitions in RDDs returned by transformations like join, reduceByKey, and parallelize when not set explicitly by the user....
spark.default.parallelism For distributed shuffle operations like reduceByKey and join, the largest number of partitions in a parent RDD. For operations like parallelize with no parent RDDs, it depends on the cluster manager:Local mode: number of cores on the local machineMesos fine grained mode...
从这里的答案来看，spark.sql.shuffle.partitions配置为联接或聚合洗牌数据时使用的分区数。spark.default....
spark.default.parallelism对于处理RDD有效; spark.sql.shuffle.partitions 这个参数带了sql,顾名思义,这是参数在执行sql的时候有效,需要注意的是,比如这个参数配置的100,sql在执行insert操作,那么插入表的hadoop目录中的文件数会和这个参数配置的数量一致;hadoop目录数,可以使用 hadoop fs -count + 目录地址进行查看,...
首先,让我们来看下它们的定义 看起来它们的定义似乎也很相似,但在实际测试中, spark.default.parallelism只有在处理RDD时才会起作用,对Spark SQL的无效。 spark.sql.shuffle.partitions则是对sparks SQL专用的设置
实战 \ Python3实战Spark大数据分析及调度 spark.sql.shuffle.partitions 与 spark.default.parallelism 的区别 老师,这两个参数,一般生产环境会配置吗?我查了一下 spark doc,感觉两者的描述很相似,分不出啥区别来啊pain7 2021-06-14 12:51:00 源自:6-12 -Spark Shuffle概述 ...
spark.sql.shuffle.partitions和spark.default.parallelism的深入理解,程序员大本营,技术文章内容聚合第一站。
It controls the number of partitions generated |> results in smaller partitions |> more likely that each partition fits into memory. The theoretical limit for SF10K seems to be 2720 based on numPersons / blockSize. I admit this name is unintuitive, but it follows the Spark naming. Member ...
assert(spark.table("t2").rdd.partitions.length == 2) sql("CACHE TABLE t3") assert(spark.table("t3").rdd.partitions.length == 2) }7 changes: 5 additions & 2 deletions 7 sql/core/src/test/scala/org/apache/spark/sql/DataFrameSetOperationsSuite.scala Original file line numberDiff line ...
set hive.exec.max.dynamic.partitions=2000;--设置动态分区时的分区最大数量 set mapred.reduce.tasks = 20;--设置reduce的任务数量,可用于优化插入分区表时的执行效率 set hive.exec.reducers.max=100;--设置reduce最大数量 set spark.executor.cores=4;--设置每个executor用的core ...