phoenix 索引实践

2020-06-19 10:31:48 浏览数 (1)

准备工作 创建测试表

代码语言:javascript复制
CREATE TABLE my_table (
        rowkey VARCHAR NOT NULL PRIMARY KEY,
        v1 VARCHAR,
         v2 VARCHAR,
         v3 VARCHAR
     );

    UPSERT INTO my_table values('1','value1','value2','value3');
    UPSERT INTO my_table values('2','value1','value2','value3');
    UPSERT INTO my_table values('3','value1','value2','value3');
    UPSERT INTO my_table values('4','value1','value2','value3');
    UPSERT INTO my_table values('5','value1','value2','value3');

开启索引支持 HBase --> 配置 --> 高级 --> 搜索 hbase-site.xml。 在服务端添加下面配置:

代码语言:javascript复制
    <property>
      <name>hbase.regionserver.wal.codec</name>
      <value>org.apache.hadoop.hbase.regionserver.wal.IndexedWALEditCodec</value>
    </property>

在这里插入图片描述

创建索引 全局索引 全局索引适合读多写少的场景。如果使用全局索引,读数据基本不损耗性能,所有的性能损耗都来源于写数据。数据表的添加、删除和修改都会更新相关的索引表(数据删除了,索引表中的数据也会删除;数据增加了,索引表的数据也会增加)。 注意: 对于全局索引在默认情况下,在查询语句中检索的列如果不在索引表中,Phoenix不会使用索引表将,除非使用hint。 创建全局索引

代码语言:javascript复制
    CREATE INDEX my_index ON my_table ( v3 );

查看效果

代码语言:javascript复制
 0: jdbc:phoenix:> select v3 from my_table where v3 = '13000010030';
     -------------- 
    |      V3      |
     -------------- 
    | 13000010030  |
     -------------- 
    1 row selected (2.155 seconds)
    0: jdbc:phoenix:> select * from my_table where v3 = '13000010030';
     ------------------- ------ -------- -------------- 
    |      ROWKEY       |  V1  |   V2   |      V3      |
     ------------------- ------ -------- -------------- 
    | 77a9ede22e169683  | aaa| bbb| 13000010030  |
     ------------------- ------ -------- -------------- 
    1 row selected (2.337 seconds)
    0: jdbc:phoenix:> CREATE INDEX my_index ON my_table ( v3 );
    1,076,190 rows affected (33.875 seconds)
    0: jdbc:phoenix:> select * from my_table where v3 = '13000010030';
     ------------------- ------ -------- -------------- 
    |      ROWKEY       |  V1  |   V2   |      V3      |
     ------------------- ------ -------- -------------- 
    | 77a9ede22e169683  | aaa| bbb| 13000010030  |
     ------------------- ------ -------- -------------- 
    1 row selected (3.296 seconds)
    0: jdbc:phoenix:> select v3 from my_table where v3 = '13000010030';
     -------------- 
    |      V3      |
     -------------- 
    | 13000010030  |
     -------------- 
    1 row selected (0.02 seconds)

本地索引 本地索引适合写多读少的场景,或者存储空间有限的场景。和全局索引一样,Phoenix也会在查询的时候自动选择是否使用本地索引。本地索引因为索引数据和原数据存储在同一台机器上,避免网络数据传输的开销,所以更适合写多的场景。由于无法提前确定数据在哪个Region上,所以在读数据的时候,需要检查每个Region上的数据从而带来一些性能损耗。 注意: 对于本地索引,查询中无论是否指定hint或者是查询的列是否都在索引表中,都会使用索引表。 创建本地索引 CREATE LOCAL INDEX LOCAL_IDEX ON my_table(v3); 查看效果

代码语言:javascript复制
0: jdbc:phoenix:> select * from my_table where v3 = '13000010030';
     ------------------- ------ -------- -------------- 
    |      ROWKEY       |  V1  |   V2   |      V3      |
     ------------------- ------ -------- -------------- 
    | 77a9ede22e169683  | aaa| bbb| 13000010030  |
     ------------------- ------ -------- -------------- 
    1 row selected (3.545 seconds)
    0: jdbc:phoenix:> select v3 from my_table where v3 = '13000010030';
     -------------- 
    |      V3      |
     -------------- 
    | 13000010030  |
     -------------- 
    1 row selected (2.946 seconds)
    0: jdbc:phoenix:> CREATE LOCAL INDEX LOCAL_IDEX ON my_table(v3);
    1,076,190 rows affected (24.67 seconds)
    0: jdbc:phoenix:> select * from my_table where v3 = '13000010030';
     ------------------- ------ -------- -------------- 
    |      ROWKEY       |  V1  |   V2   |      V3      |
     ------------------- ------ -------- -------------- 
    | 77a9ede22e169683  | aaa| bbb| 13000010030  |
     ------------------- ------ -------- -------------- 
    1 row selected (0.055 seconds)
    0: jdbc:phoenix:> select v3 from my_table where v3 = '13000010030';
     -------------- 
    |      V3      |
     -------------- 
    | 13000010030  |
     -------------- 
    1 row selected (0.013 seconds)

覆盖索引 覆盖索引是把原数据存储在索引数据表中,这样在查询时不需要再去HBase的原表获取数据就,直接返回查询结果。 注意: 查询是 select 的列和 where 的列都需要在索引中出现。 创建覆盖索引 CREATE INDEX my_index ON my_table ( v2,v3 ) INCLUDE ( v1 ); 添加索引后提升到毫秒级

代码语言:javascript复制
0: jdbc:phoenix:> select * from my_table where v3 = '13308117837' and v2 = '北京顺义';
     ------------------- ----- ------- -------------- 
    |      ROWKEY       | V1  |  V2   |      V3      |
     ------------------- ----- ------- -------------- 
    | 3f65283ed7553909  | wenyuan  | ccc| 13308117837  |
     ------------------- ----- ------- -------------- 
    1 row selected (2.42 seconds)
    0: jdbc:phoenix:> CREATE INDEX my_index ON my_table (v2,v3) INCLUDE ( v1 );
    1,076,190 rows affected (47.432 seconds)
    0: jdbc:phoenix:> select * from my_table where v3 = '13308117837' and v2 = '北京顺义';
     ------------------- ----- ------- -------------- 
    |      ROWKEY       | V1  |  V2   |      V3      |
     ------------------- ----- ------- -------------- 
    | 3f65283ed7553909  | wenyuan| ccc| 13308117837  |
     ------------------- ----- ------- -------------- 
    1 row selected (0.031 seconds)

函数索引 从Phoenix4.3版本就有函数索引,特点是索引的内容不局限于列,能根据表达式创建索引。适用于对查询表时过滤条件是表达式。如果你使用的表达式正好就是索引的话,数据也可以直接从这个索引获取,而不需要从数据库获取。 创建索引 CREATE INDEX my_index ON my_table(substr(v3,1,9)) INCLUDE ( v1 ); 查看效果

代码语言:javascript复制
0: jdbc:phoenix:> select v1,substr(v3,1,9) from my_table where substr(v3,1,9) = '130000109';
     ----- ------------------- 
    | V1  | SUBSTR(V3, 1, 9)  |
     ----- ------------------- 
    | wenyuan| 130000109         |
     ----- ------------------- 
    1 row selected (3.656 seconds)
    0: jdbc:phoenix:> select v1,v3 from my_table where substr(v3,1,9) = '130000109';
     ----- -------------- 
    | V1  |      V3      |
     ----- -------------- 
    | wenyuan| 13000010979  |
     ----- -------------- 
    1 row selected (3.969 seconds)
    0: jdbc:phoenix:> CREATE INDEX my_index ON my_table(substr(v3,1,9)) INCLUDE ( v1 );
    1,076,190 rows affected (45.833 seconds)

    0: jdbc:phoenix:> select v1,v3 from my_table where substr(v3,1,9) = '130000109';
     ----- -------------- 
    | V1  |      V3      |
     ----- -------------- 
    | wenyuan| 13000010979  |
     ----- -------------- 
    1 row selected (3.44 seconds)
    0: jdbc:phoenix:> select v1,v3,substr(v3,1,9) from my_table where substr(v3,1,9) = '130000109';
     ----- -------------- ------------------- 
    | V1  |      V3      | SUBSTR(V3, 1, 9)  |
     ----- -------------- ------------------- 
    | wenyuan| 13000010979  | 130000109         |
     ----- -------------- ------------------- 
    1 row selected (3.327 seconds)
    0: jdbc:phoenix:> select v1,substr(v3,1,9) from my_table where substr(v3,1,9) = '130000109';
     ----- -------------------- 
    | V1  | " SUBSTR(V3,1,9)"  |
     ----- -------------------- 
    | wenyuan  | 130000109          |
     ----- -------------------- 
    1 row selected (0.013 seconds)
    0: jdbc:phoenix:> select v1 from my_table where substr(v3,1,9) = '130000109';
     ----- 
    | V1  |
     ----- 
    | wenyuan|
     ----- 
    1 row selected (0.011 seconds)

索引Building 同步索引

代码语言:javascript复制
    CREATE INDEX ASYNC_IDX ON SCHEMA_NAME.TABLE_NAME(BASICINFO."s1",BASICINFO."s2") ;

创建同步索引超时怎么办? 在客户端配置文件hbase-site.xml中,把超时参数设置大一些,足够 Build 索引数据的时间。

代码语言:javascript复制
 <property>
        <name>hbase.rpc.timeout</name>
        <value>60000000</value>
    </property>
    <property>
        <name>hbase.client.scanner.timeout.period</name>
        <value>60000000</value>
    </property>
    <property>
        <name>phoenix.query.timeoutMs</name>
        <value>60000000</value>
    </property>

异步索引 异步Build索引需要借助MapReduce,创建异步索引语法和同步索引相差一个关键字:ASYNC。 创建异步索引

代码语言:javascript复制
        CREATE INDEX ASYNC_IDX ON SCHEMA_NAME.TABLE_NAME ( BASICINFO."s1", BASICINFO."s2" ) ASYNC;
    

运行MapReduce 执行MapReduce

代码语言:javascript复制
        hbase org.apache.phoenix.mapreduce.index.IndexTool 
        --schema SCHEMA_NAME
        --data-table TABLE_NAME
        --index-table ASYNC_IDX 
        --output-path ASYNC_IDX_HFILES

日志:

代码语言:javascript复制
Java HotSpot(TM) 64-Bit Server VM warning: Using incremental CMS is deprecated and will likely be removed in a future release
        SLF4J: Class path contains multiple SLF4J bindings.
        SLF4J: Found binding in [jar:file:/opt/cloudera/parcels/CDH-5.12.1-1.cdh5.12.1.p0.3/jars/phoenix-4.14.0-cdh5.12.2-client.jar!/org/slf4j/impl/StaticLoggerBinder.class]
        SLF4J: Found binding in [jar:file:/opt/cloudera/parcels/CDH-5.12.1-1.cdh5.12.1.p0.3/jars/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
        SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
        SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
        19/05/22 15:38:41 INFO log.QueryLoggerDisruptor: Starting  QueryLoggerDisruptor for with ringbufferSize=8192, waitStrategy=BlockingWaitStrategy, exceptionHandler=org.apache.phoenix.log.QueryLoggerDefaultExceptionHandler@dd0c991...
        19/05/22 15:38:41 INFO query.ConnectionQueryServicesImpl: An instance of ConnectionQueryServices was created.

        ...

        19/05/22 15:41:19 INFO index.IndexTool: Loading HFiles from INDEX_PERSONAS_TAG_HFILES/MY_SCHEMA.INDEX_PERSONAS_TAG
        19/05/22 15:41:19 WARN mapreduce.LoadIncrementalHFiles: Skipping non-directory hdfs://bigdata-dev-41:8020/user/root/INDEX_PERSONAS_TAG_HFILES/MY_SCHEMA.INDEX_PERSONAS_TAG/_SUCCESS
        19/05/22 15:41:19 INFO hfile.CacheConfig: CacheConfig:disabled
        19/05/22 15:41:19 INFO mapreduce.LoadIncrementalHFiles: Trying to load hfile=hdfs://bigdata-dev-41:8020/user/root/INDEX_PERSONAS_TAG_HFILES/MY_SCHEMA.INDEX_PERSONAS_TAG/0/e1f766365b4f4c7cb6cfc6e0d18328b8 first=0x0010x00xE4xB8x9AxE4xB8xBBx000x000x0010x000x00xE6xADxA3xE5xB8xB8xE4xB8x9AxE4xB8xBBx001001.99x000x001x003x00xE8x80x81xE5xAExA2xE6x88xB7x00xE6x9CxAAxE7x9FxA5x0042471415705946377 last=2x009x00xE7xA7x9FxE5xAExA2x002x002x009x002x00xE9x95xBFxE6x9Cx9FxE4xB8x8DxE4xBAxA4xE7x89xA9xE4xB8x9AxE7xAExA1xE7x90x86xE8xB4xB9x00988.56x000x001x004x00xE6x9CxAAxE7x9FxA5x00xE5x9Cx9FxE8xB1xAAx0044ff3613003558171
        19/05/22 15:41:20 INFO index.IndexToolUtil:  Updated the status of the index INDEX_PERSONAS_TAG to ACTIVE

遇到问题 Error: Could not find or load main class org.apache.phoenix.mapreduce.index.IndexTool 解决办法 将 phoenix-4.14.0-cdh5.12.2-client.jar 包复制到 hbase 的 lib 目录下 [root@node00 ~]# cd /opt/cloudera/parcels/ [root@node00 parcels]# cd APACHE_PHOENIX/lib/phoenix [root@node00 phoenix]# cp phoenix-4.14.0-cdh5.12.2-client.jar /opt/cloudera/parcels/CDH/jars/ [root@node00 phoenix]# cd /opt/cloudera/parcels/CDH/lib/hbase/lib/ [root@node00 lib]# ln -s ../../../jars/phoenix-4.14.0-cdh5.12.2-client.jar phoenix-4.14.0-cdh5.12.2-client.jar 索引用法总结 Phoenix 的二级索引主要有两种,即全局索引和本地索引。 全局索引适合读多写少的场景,如果使用全局索引,读数据基本不损耗性能,所有的性能损耗都来源于写数据。 本地索引适合写多读少的场景,或者存储空间有限的场景。 索引定义完之后,一般来说,Phoenix自己会判定使用哪个索引更加有效。 但是,全局索引必须是查询语句中所有列都包含在全局索引中,它才会生效。 索引为:

代码语言:javascript复制
create index my_index on my_table (v3);

select v1 from my_table where v3 = '13406157616';

上面语句怎样才能使用索引呢? 有以下三种方法使它使用索引: 使用覆盖索引

代码语言:javascript复制
    CREATE INDEX cover_index ON my_table(v3) INCLUDE (v1);

查看效果

代码语言:javascript复制
    0: jdbc:phoenix:> select v1 from my_table where v3 = '13406157616';
     ------ 
    |  V1  |
     ------ 
    | wenyuan|
     ------ 
    1 row selected (0.01 seconds)

使用 Hint 强制索引

代码语言:javascript复制
SELECT /*  INDEX(my_table my_index) */ v1 FROM my_table WHERE v3 = '13406157616';

查看效果

代码语言:javascript复制
    0: jdbc:phoenix:> SELECT /*  INDEX(my_table my_index) */ v1 FROM my_table WHERE v3 = '13406157616';
     ------ 
    |  V1  |
     ------ 
    | wenyuan|
     ------ 
    1 row selected (0.044 seconds)

使用本地索引

代码语言:javascript复制
    CREATE LOCAL INDEX local_index on my_table (v3);

查看效果

代码语言:javascript复制
0: jdbc:phoenix:> select v1 from my_table where v3 = '13406157616';
     ------ 
    |  V1  |
     ------ 
    | wenyuan|
     ------ 
    1 row selected (0.025 seconds)

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