java.lang.OutOfMemoryError:带有蜂巢的Java堆空间
问题内容:
我使用了hadoop hive 0.9.0和1.1.2以及netbeans,但是出现了这个错误,但是我不能解决这个问题,请帮我编码:
public class Hive_test {
private static String driverName = "org.apache.hadoop.hive.jdbc.HiveDriver";
@SuppressWarnings("CallToThreadDumpStack")
public static void main(String[] args) throws SQLException {
try {
Class.forName(driverName);
} catch (ClassNotFoundException e){
e.printStackTrace();
System.exit(1);
}
System.out.println("commencer la connexion");
Connection con = DriverManager.getConnection("jdbc:hive://localhost:10000/default",""," ");
Statement stmt = con.createStatement();
ResultSet res = stmt.executeQuery("select * from STATE");
while (res.next()){
System.out.println(String.valueOf(res.getInt(1)) + "\t" + res.getString(2));
System.out.println("sql terminer");
}
}
以下错误;
error :
commencer la connexion
Exception in thread "main" java.lang.OutOfMemoryError: Java heap space
at org.apache.thrift.protocol.TBinaryProtocol.readStringBody(TBinaryProtocol.java:353)
at org.apache.thrift.protocol.TBinaryProtocol.readMessageBegin(TBinaryProtocol.java:215)
at org.apache.thrift.TServiceClient.receiveBase(TServiceClient.java:69)
at org.apache.hadoop.hive.service.ThriftHive$Client.recv_execute(ThriftHive.java:116)
at org.apache.hadoop.hive.service.ThriftHive$Client.execute(ThriftHive.java:103)
at org.apache.hadoop.hive.jdbc.HiveStatement.executeQuery(HiveStatement.java:192)
at org.apache.hadoop.hive.jdbc.HiveStatement.execute(HiveStatement.java:132)
at org.apache.hadoop.hive.jdbc.HiveConnection.configureConnection(HiveConnection.java:132)
at org.apache.hadoop.hive.jdbc.HiveConnection.<init>(HiveConnection.java:122)
at org.apache.hadoop.hive.jdbc.HiveDriver.connect(HiveDriver.java:106)
at java.sql.DriverManager.getConnection(DriverManager.java:571)
at java.sql.DriverManager.getConnection(DriverManager.java:215)
at hive.Hive_test.main(Hive_test.java:22)
问题答案:
您可以在Hive中设置容器的堆大小并解决此错误:
在Hadoop
MapReduce框架上运行的大多数工具都提供了为作业调整这些Hadoop级别设置的方法。Hive中有多种方法可以做到这一点。其中三个显示在这里:
1)通过Hive命令行直接传递它:
hive -hiveconf mapreduce.map.memory.mb=4096 -hiveconf mapreduce.reduce.memory.mb=5120 -e "select count(*) from test_table;"
2)在调用Hive之前设置ENV变量:
export HIVE_OPTS="-hiveconf mapreduce.map.memory.mb=4096 -hiveconf mapreduce.reduce.memory.mb=5120"
3)在配置单元CLI中使用“ set”命令。
hive> set mapreduce.map.memory.mb=4096;
hive> set mapreduce.reduce.memory.mb=5120;
hive> select count(*) from test_table;