Skip to content

none12 compression does not exist - none was meant #4

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
lbruand wants to merge 2 commits into
base: master
Choose a base branch
from
Open

none12 compression does not exist - none was meant #4

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
b9bfa28
none12 compression does not exist - none was meant
lbruand Feb 27, 2021
d925138
Improved console output - showing the AQE status
lbruand Feb 27, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion src/main/scala/com/sparkbyexamples/spark/dataframe/examples/ReadORCFile.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@ object ReadORCFile extends App{
.orc("/tmp/orc/data.orc")

df.write.mode("overwrite")
.option("compression","none12")
.option("compression","none")
.orc("/tmp/orc/data-nocomp.orc")

df.write.mode("overwrite")
Expand Down
11 changes: 5 additions & 6 deletions ...byexamples/spark/spark30/ADQExample.scala → ...byexamples/spark/spark30/AQEExample.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@ package com.sparkbyexamples.spark.spark30

import org.apache.spark.sql.SparkSession

object ADQExample extends App{
object AQEExample extends App{

val spark: SparkSession = SparkSession.builder()
.master("local[5]")
Expand All @@ -25,12 +25,11 @@ object ADQExample extends App{
val df = simpleData.toDF("employee_name","department","state","salary","age","bonus")

val df1=df.groupBy("department").count()
println(df1.rdd.getNumPartitions)

spark.conf.set("spark.sql.adaptive.enabled",200)
val df2=df.groupBy("department").count()
println(df2.rdd.getNumPartitions)

println(s"Number of partitions in RDD (AQE=[${spark.conf.get("spark.sql.adaptive.enabled")}]) = [${df1.rdd.getNumPartitions}]")

spark.conf.set("spark.sql.adaptive.enabled", true)

val df2=df.groupBy("department").count()
println(s"Number of partitions in RDD (AQE=[${spark.conf.get("spark.sql.adaptive.enabled")}]) = [${df2.rdd.getNumPartitions}]")
}