Mapreduce atop Apache Phoenix (ScanPlan 初探)
利用Mapreduce/hive查询Phoenix数据时如何划分partition?
PhoenixInputFormat
的源码一看便知:
public List<InputSplit> getSplits(JobContext context) throws IOException, InterruptedException {
Configuration configuration = context.getConfiguration();
QueryPlan queryPlan = this.getQueryPlan(context, configuration);
List allSplits = queryPlan.getSplits();
List splits = this.generateSplits(queryPlan, allSplits);
return splits;
}
根据select查询语句创建查询计划,QueryPlan,实际是子类ScanPlan。getQueryPlan
函数有一个特殊操作:
queryPlan.iterator(MapReduceParallelScanGrouper.getInstance());
如果HBase表有多个Region,则会将一个Scan
划分为多个,每个Region对应一个Split。这个逻辑跟MR on HBase类似。只是这边的实现过程不同,这边调用的是Phoenix的QueryPlan,而不是HBase API。
以下是一个示例,加深这一过程的理解。
Phoenix 建表
将表presplit为4个region:[-∞,CS), [CS, EU), [EU, NA), [NA, +∞)
CREATE TABLE TEST (HOST VARCHAR NOT NULL PRIMARY KEY, DESCRIPTION VARCHAR) SPLIT ON ('CS','EU','NA');
upsert into test(host, description) values ('CS11', 'cccccccc');
upsert into test(host, description) values ('EU11', 'eeeddddddddd')
upsert into test(host, description) values ('NA11', 'nnnnneeeddddddddd');
0: jdbc:phoenix:localhost> select * from test;
+-------+--------------------+
| HOST | DESCRIPTION |
+-------+--------------------+
| CS11 | cccccccc |
| EU11 | eeeddddddddd |
| NA11 | nnnnneeeddddddddd |
+-------+--------------------+
窥探ScanPlan
import org.apache.hadoop.hbase.client.Scan;
import org.apache.log4j.BasicConfigurator;
import org.apache.phoenix.compile.QueryPlan;
import org.apache.phoenix.iterate.MapReduceParallelScanGrouper;
import org.apache.phoenix.jdbc.PhoenixStatement;
import java.io.IOException;
import java.sql.*;
import java.util.List;
public class LocalPhoenix {
public static void main(String[] args) throws SQLException, IOException {
BasicConfigurator.configure();
Statement stmt = null;
ResultSet rs = null;
Connection con = DriverManager.getConnection("jdbc:phoenix:localhost:2181:/hbase");
stmt = con.createStatement();
PhoenixStatement pstmt = (PhoenixStatement)stmt;
QueryPlan queryPlan = pstmt.optimizeQuery("select * from TEST");
queryPlan.iterator(MapReduceParallelScanGrouper.getInstance());
Scan scan = queryPlan.getContext().getScan();
List<List<Scan>> scans = queryPlan.getScans();
for (List<Scan> sl : scans) {
System.out.println();
for (Scan s : sl) {
System.out.print(s);
}
}
con.close();
}
}
4个scan如下:
{"loadColumnFamiliesOnDemand":null,"startRow":"","stopRow":"CS","batch":-1,"cacheBlocks":true,"totalColumns":1,"maxResultSize":-1,"families":{"0":["ALL"]},"caching":100,"maxVersions":1,"timeRange":[0,1523338217847]}
{"loadColumnFamiliesOnDemand":null,"startRow":"CS","stopRow":"EU","batch":-1,"cacheBlocks":true,"totalColumns":1,"maxResultSize":-1,"families":{"0":["ALL"]},"caching":100,"maxVersions":1,"timeRange":[0,1523338217847]}
{"loadColumnFamiliesOnDemand":null,"startRow":"EU","stopRow":"NA","batch":-1,"cacheBlocks":true,"totalColumns":1,"maxResultSize":-1,"families":{"0":["ALL"]},"caching":100,"maxVersions":1,"timeRange":[0,1523338217847]}
{"loadColumnFamiliesOnDemand":null,"startRow":"NA","stopRow":"","batch":-1,"cacheBlocks":true,"totalColumns":1,"maxResultSize":-1,"families":{"0":["ALL"]},"caching":100,"maxVersions":1,"timeRange":[0,1523338217847]}Disconnected from the target VM, address: '127.0.0.1:63406', transport: 'socket'
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