[
https://issues.apache.org/jira/browse/SPARK-10529?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
ZhengYaofeng updated SPARK-10529:
---------------------------------
Description:
Test code as follows:
object SqlTest {
def main(args: Array[String]) {
def createSc = {
val sparkConf = new SparkConf().setAppName(s"SqlTest")
.setMaster("spark://zdh221:7077")
.set("spark.executor.memory", "4g")
.set("spark.executor.cores", "2")
.set("spark.cores.max", "6")
new SparkContext(sparkConf)
}
for (index <- 1 to 200) {
println(s"============Current Index:${index}=============")
val hc = new HiveContext(createSc)
hc.sql("show databases").collect().foreach(println)
hc.sparkContext.stop()
Thread.sleep(3000)
}
Thread.sleep(1000000)
}
}
Testing on spark 1.4.1 with run cmd bellow.
export
CLASSPATH="$CLASSPATH:/home/hadoop/spark/conf:/home/hadoop/spark/lib/*:/home/hadoop/zyf/lib/*"
java -Xmx8096m -Xms1024m -XX:MaxPermSize=1024m -cp $CLASSPATH SqlTest
Files list:
/home/hadoop/spark/conf:core-site.xml;hdfs-site.xml;hive-site.xml;slaves;spark-defaults.conf;spark-env.sh
/home/hadoop/zyf/lib:hadoop-lzo-0.4.20.jar;mysql-connector-java-5.1.28-bin.jar;sqltest-1.0-SNAPSHOT.jar
MySQL is used as the metastore. You can obviously see that jdbc connections to
MySQL grow constantly through command 'show status like 'Threads_connected';'
when my test app is running. Even if you invoke 'Hive.closeCurrent()', it
cann't release current jdbc connections. Besides I can not find another
possible way. If you take spark 1.3.1 to test, jdbc connections won't grow.
Meanwhile, it ends with 'java.lang.OutOfMemoryError: PermGen space' when
cycling 45 times, which means 45 HiveContext objects are created. It's
interesting that if you set MaxPermSize to '2048m', it can cycle 93 times, if
you set MaxPermSize to '3072m', it can cycle 141 times. So,it indicates that
each time creating one HiveContext object, it loads the same amount of new
classes and they won't be released.
was:
Test code as follows:
object SqlTest {
def main (args: Array[String]) {
var port = 4042
def createSc = {
val sparkConf = new SparkConf().setAppName(s"SqlTest_$port")
.setMaster("spark://zdh221:7077")
.set("spark.ui.port",port.toString)
.set("spark.executor.memory","4g")
.set("spark.executor.cores","2")
.set("spark.cores.max","6")
port += 1
new SparkContext(sparkConf)
}
while(port - 4042 < 200){
println(s"============Current app id:${port - 4042}=============")
val hc = new HiveContext(createSc)
hc.sql("show databases").collect().foreach(println)
hc.sparkContext.stop()
//Hive.closeCurrent()
//hc = null
Thread.sleep(3000)
}
Thread.sleep(1000000)
}
}
Testing on spark 1.4.1 with run cmd bellow.
export
CLASSPATH="$CLASSPATH:/home/hadoop/spark/conf:/home/hadoop/spark/lib/*:/home/hadoop/zyf/lib/*"
java -Xmx8096m -Xms1024m -XX:MaxPermSize=1024m -cp $CLASSPATH SqlTest
Files list:
/home/hadoop/spark/conf:core-site.xml;hdfs-site.xml;hive-site.xml;slaves;spark-defaults.conf;spark-env.sh
/home/hadoop/zyf/lib:hadoop-lzo-0.4.20.jar;mysql-connector-java-5.1.28-bin.jar;sqltest-1.0-SNAPSHOT.jar
MySQL is used as the metastore. You can obviously see that jdbc connections to
MySQL grow constantly through command 'show status like 'Threads_connected';'
when my test app is running. Even if you invoke 'Hive.closeCurrent()', it
cann't release current jdbc connections. Besides I can not find another
possible way. If you take spark 1.3.1 to test, jdbc connections won't grow.
Meanwhile, it ends with 'java.lang.OutOfMemoryError: PermGen space' when
cycling 45 times, which means 45 HiveContext objects are created. It's
interesting that if you set MaxPermSize to '2048m', it can cycle 93 times, if
you set MaxPermSize to '3072m', it can cycle 141 times. So,it indicates that
each time creating one HiveContext object, it loads the same amount of new
classes and they won't be released.
> When creating multiple HiveContext objects in one jvm, jdbc connections to
> metastore cann't be released and it may cause PermGen OutOfMemoryError.
> --------------------------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-10529
> URL: https://issues.apache.org/jira/browse/SPARK-10529
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.4.1
> Reporter: ZhengYaofeng
> Attachments: IsolatedClientLoader.scala
>
>
> Test code as follows:
> object SqlTest {
> def main(args: Array[String]) {
> def createSc = {
> val sparkConf = new SparkConf().setAppName(s"SqlTest")
> .setMaster("spark://zdh221:7077")
> .set("spark.executor.memory", "4g")
> .set("spark.executor.cores", "2")
> .set("spark.cores.max", "6")
> new SparkContext(sparkConf)
> }
> for (index <- 1 to 200) {
> println(s"============Current Index:${index}=============")
> val hc = new HiveContext(createSc)
> hc.sql("show databases").collect().foreach(println)
> hc.sparkContext.stop()
> Thread.sleep(3000)
> }
> Thread.sleep(1000000)
> }
> }
>
> Testing on spark 1.4.1 with run cmd bellow.
> export
> CLASSPATH="$CLASSPATH:/home/hadoop/spark/conf:/home/hadoop/spark/lib/*:/home/hadoop/zyf/lib/*"
> java -Xmx8096m -Xms1024m -XX:MaxPermSize=1024m -cp $CLASSPATH SqlTest
> Files list:
>
> /home/hadoop/spark/conf:core-site.xml;hdfs-site.xml;hive-site.xml;slaves;spark-defaults.conf;spark-env.sh
>
> /home/hadoop/zyf/lib:hadoop-lzo-0.4.20.jar;mysql-connector-java-5.1.28-bin.jar;sqltest-1.0-SNAPSHOT.jar
>
> MySQL is used as the metastore. You can obviously see that jdbc connections
> to MySQL grow constantly through command 'show status like
> 'Threads_connected';' when my test app is running. Even if you invoke
> 'Hive.closeCurrent()', it cann't release current jdbc connections. Besides I
> can not find another possible way. If you take spark 1.3.1 to test, jdbc
> connections won't grow.
> Meanwhile, it ends with 'java.lang.OutOfMemoryError: PermGen space' when
> cycling 45 times, which means 45 HiveContext objects are created. It's
> interesting that if you set MaxPermSize to '2048m', it can cycle 93 times, if
> you set MaxPermSize to '3072m', it can cycle 141 times. So,it indicates that
> each time creating one HiveContext object, it loads the same amount of new
> classes and they won't be released.
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