如何计算Spark Scala中数据框的大小 [英] How to calculate size of dataframe in spark scala

问题描述

我想编写一个带有重新分区的大型数据框，所以我想计算源数据框的重新分区数.

I want to write one large sized dataframe with repartition so i want to calculate number of repartition for my source dataframe.

numberofpartition = {数据帧的大小/default_blocksize}

numberofpartition= {size of dataframe/default_blocksize}

所以请告诉我如何计算Spark Scala中数据框的大小

so please tell me how to calculate size of dataframe in spark scala

预先感谢.

推荐答案

使用spark.sessionState.executePlan(df.queryExecution.logical).optimizedPlan.stats(spark.sessionState.conf).sizeInBytes，一旦将其加载到内存中，我们便可以获取实际Dataframe的大小，例如，您可以检查以下代码.

Usingspark.sessionState.executePlan(df.queryExecution.logical).optimizedPlan.stats(spark.sessionState.conf).sizeInBytes we can get the size of actual Dataframe once its loaded into memory, for example you can check below code.

scala> val df = spark.read.format("orc").load("/tmp/srinivas/")
df: org.apache.spark.sql.DataFrame = [channelGrouping: string, clientId: string ... 75 more fields]

scala> import org.apache.commons.io.FileUtils
import org.apache.commons.io.FileUtils

scala> val bytes = spark.sessionState.executePlan(df.queryExecution.logical).optimizedPlan.stats(spark.sessionState.conf).sizeInBytes
bytes: BigInt = 763275709

scala> FileUtils.byteCountToDisplaySize(bytes.toLong)
res5: String = 727 MB

scala> import sys.process._
import sys.process._

scala> "hdfs dfs -ls -h /tmp/srinivas/".!
Found 2 items
-rw-r-----   3 svcmxns hdfs          0 2020-04-20 01:46 /tmp/srinivas/_SUCCESS
-rw-r-----   3 svcmxns hdfs    727.4 M 2020-04-20 01:46 /tmp/srinivas/part-00000-9d0b72ea-f617-4092-ae27-d36400c17917-c000.snappy.orc
res6: Int = 0

val bytes = spark.sessionState.executePlan(df.queryExecution.logical).optimizedPlan.stats(spark.sessionState.conf).sizeInBytes
    val dataSize = bytes.toLong
    val numPartitions = (bytes.toLong./(1024.0)./(1024.0)./(10240)).ceil.toInt // May be you can change or modify this to get required partitions.

    df.repartition(if(numPartitions == 0) 1 else numPartitions)
      .[...]

Edit - 1:请根据您的spark版本使用以下逻辑.

Edit - 1 : Please use below logic as per your spark versions.

火花2.4

val bytes = spark.sessionState.executePlan(df.queryExecution.logical).optimizedPlan.stats(spark.sessionState.conf).sizeInBytes

火花2.3

val bytes = spark.sessionState.executePlan(df.queryExecution.logical).optimizedPlan.stats.sizeInBytes

对于Python

spark._jsparkSession.sessionState().executePlan(df._jdf.queryExecution().logical()).optimizedPlan().stats().sizeInBytes()

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