我正在为POC探索impala，我的任务是添加10亿行，并检查我们可以多快地插入和检索数据。 我创建了一个表，该表有30行，其中一半是字符串，2是时间戳，其余是整数。它花费了将近3个小时来添加100万行，但生产速度非常慢。
我编写了一个小的Java代码，其中以1000个批处理的方式插入数据，该代码非常慢，花了将近13个小时才添加400万行。
private static Connection connectViaDS() throws Exception {
Connection connection = null;
Class.forName("com.cloudera.impala.jdbc41.Driver");
connection = DriverManager.getConnection(CONNECTION_URL);
return connection;
}
private static void writeInABatchWithCompiledQuery(int records) {
int protocol_no = 233,s_port=20,d_port=34,packet=46,volume=58,duration=39,pps=76,
bps=65,bpp=89,i_vol=465,e_vol=345,i_pkt=5,e_pkt=54,s_i_ix=654,d_i_ix=444,_time=1000,flow=989;
String s_city = "Mumbai",s_country = "India", s_latt = "12.165.34c", s_long = "39.56.32d",
s_host="motadata",d_latt="29.25.43c",d_long="49.15.26c",d_city="Damouli",d_country="Nepal";
long e_date= 1275822966, e_time= 1370517366;
PreparedStatement preparedStatement;
// int total = 1000000*1000;
int total = 1000000*1000;
int counter =0;
Connection connection = null;
try {
connection = connectViaDS();
preparedStatement = connection.prepareStatement(sqlCompiledQuery);
Timestamp ed = new Timestamp(e_date);
Timestamp et = new Timestamp(e_time);
while(counter <total) {
for (int index = 1; index <= 1000; index++) {
counter++;
preparedStatement.setString(1, "s_ip" + String.valueOf(index));
// System.out.println(1);
preparedStatement.setString(2, "d_ip" + String.valueOf(index));
// System.out.println(2);
preparedStatement.setInt(3, protocol_no + index);
// System.out.println(3);
preparedStatement.setInt(4, s_port + index);
// System.out.println(4);
preparedStatement.setInt(5, d_port + index);
// System.out.println(5);
preparedStatement.setInt(6, packet + index);
// System.out.println(6);
preparedStatement.setInt(7, volume + index);
// System.out.println(7);
preparedStatement.setInt(8, duration + index);
// System.out.println(8);
preparedStatement.setInt(9, pps + index);
// System.out.println(9);
preparedStatement.setInt(10, bps + index);
// System.out.println(10);
preparedStatement.setInt(11, bpp + index);
// System.out.println(11);
preparedStatement.setString(12, s_latt + String.valueOf(index));
// System.out.println(12);
preparedStatement.setString(13, s_long + String.valueOf(index));
// System.out.println(13);
preparedStatement.setString(14, s_city + String.valueOf(index));
// System.out.println(14);
preparedStatement.setString(15, s_country + String.valueOf(index));
// System.out.println(15);
preparedStatement.setString(16, d_latt + String.valueOf(index));
// System.out.println(16);
preparedStatement.setString(17, d_long + String.valueOf(index));
// System.out.println(17);
preparedStatement.setString(18, d_city + String.valueOf(index));
// System.out.println(18);
preparedStatement.setString(19, d_country + String.valueOf(index));
// System.out.println(19);
preparedStatement.setInt(20, i_vol + index);
// System.out.println(20);
preparedStatement.setInt(21, e_vol + index);
// System.out.println(21);
preparedStatement.setInt(22, i_pkt + index);
// System.out.println(22);
preparedStatement.setInt(23, e_pkt + index);
// System.out.println(23);
preparedStatement.setInt(24, s_i_ix + index);
// System.out.println(24);
preparedStatement.setInt(25, d_i_ix + index);
// System.out.println(25);
preparedStatement.setString(26, s_host + String.valueOf(index));
// System.out.println(26);
preparedStatement.setTimestamp(27, ed);
// System.out.println(27);
preparedStatement.setTimestamp(28, et);
// System.out.println(28);
preparedStatement.setInt(29, _time);
// System.out.println(29);
preparedStatement.setInt(30, flow + index);
// System.out.println(30);
// System.out.println(index);
preparedStatement.addBatch();
}
preparedStatement.executeBatch();
preparedStatement.clearBatch();
//System.out.println("Counter = "+counter);
}
// long start = System.currentTimeMillis();
// int[] inserted = preparedStatement.executeBatch();
// long end = System.currentTimeMillis();
// System.out.println("total time taken to insert the batch = " + (end - start) + " ms");
//System.out.println("total time taken = " + (end - start)/records + " s");
//System.out.println("Inserted: "+inserted);
} catch (Exception e) {
e.printStackTrace();
} finally {
try {
connection.close();
} catch (SQLException e) {
e.printStackTrace();
}
}
}
数据以蜗牛的速度更新，我尝试增加批量大小，但降低了速度。 我不知道我的代码是否错误，或者我需要调整Impala以获得更好的性能。请指导。
我正在使用VM进行测试，这是其他详细信息-
System.
Os - Ubuntu 16
RAM - 12 gb
Cloudera - CDH 6.2
Impala daemon limit - 2 gb
Java heap size impala daemon - 500mb
HDFS Java Heap Size of NameNode in Bytes - 500mb.
如果需要更多详细信息，请告诉我。