I want to write one large sized dataframe with repartition, so I want to calculate number of repartition for my source dataframe.
numberofpartition = {size of dataframe/default_blocksize}
How to calculate the dataframe size in bytes?
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. Check the 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
: Please use the following logic as per your Spark versions.
Spark 3.0.2
val bytes = spark.sessionState.executePlan(df.queryExecution.logical).optimizedPlan.stats.sizeInBytes
Spark 2.4
val bytes = spark.sessionState.executePlan(df.queryExecution.logical).optimizedPlan.stats(spark.sessionState.conf).sizeInBytes
Spark 2.3
val bytes = spark.sessionState.executePlan(df.queryExecution.logical).optimizedPlan.stats.sizeInBytes
PySpark
spark._jsparkSession.sessionState().executePlan(df._jdf.queryExecution().logical()).optimizedPlan().stats().sizeInBytes()