Phoenix二级索引的使用

准备工作

1. 创建测试表

    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');
    ...
   
   复制

2. 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：

    <property>
      <name>hbase.regionserver.wal.codec</name>
      <value>org.apache.hadoop.hbase.regionserver.wal.IndexedWALEditCodec</value>
    </property>
   
   复制

   

创建索引

1. 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

    CREATE INDEX my_index ON my_table ( v3 );
   
   复制

   查看效果

    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  | 麻保波  | 台湾屏东县  | 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  | 麻保波  | 台湾屏东县  | 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)
   
   复制

2. 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);
   
   复制

   查看效果

    0: jdbc:phoenix:> select * from my_table where v3 = '13000010030';
    +-------------------+------+--------+--------------+
    |      ROWKEY       |  V1  |   V2   |      V3      |
    +-------------------+------+--------+--------------+
    | 77a9ede22e169683  | 麻保波  | 台湾屏东县  | 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  | 麻保波  | 台湾屏东县  | 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)
   
   复制

3. 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 );
   
   复制

   添加索引后提升到毫秒级

    0: jdbc:phoenix:> select * from my_table where v3 = '13308117837' and v2 = '北京顺义';
    +-------------------+-----+-------+--------------+
    |      ROWKEY       | V1  |  V2   |      V3      |
    +-------------------+-----+-------+--------------+
    | 3f65283ed7553909  | 齐晨  | 北京顺义  | 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  | 齐晨  | 北京顺义  | 13308117837  |
    +-------------------+-----+-------+--------------+
    1 row selected (0.031 seconds)
   
   复制

4. 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 );
   
   复制

   查看效果

    0: jdbc:phoenix:> select v1,substr(v3,1,9) from my_table where substr(v3,1,9) = '130000109';
    +-----+-------------------+
    | V1  | SUBSTR(V3, 1, 9)  |
    +-----+-------------------+
    | 凤伊  | 130000109         |
    +-----+-------------------+
    1 row selected (3.656 seconds)
    0: jdbc:phoenix:> select v1,v3 from my_table where substr(v3,1,9) = '130000109';
    +-----+--------------+
    | V1  |      V3      |
    +-----+--------------+
    | 凤伊  | 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      |
    +-----+--------------+
    | 凤伊  | 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)  |
    +-----+--------------+-------------------+
    | 凤伊  | 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)"  |
    +-----+--------------------+
    | 凤伊  | 130000109          |
    +-----+--------------------+
    1 row selected (0.013 seconds)
    0: jdbc:phoenix:> select v1 from my_table where substr(v3,1,9) = '130000109';
    +-----+
    | V1  |
    +-----+
    | 凤伊  |
    +-----+
    1 row selected (0.011 seconds)
   
   复制

索引Building

1. 同步索引

    CREATE INDEX ASYNC_IDX ON SCHEMA_NAME.TABLE_NAME(BASICINFO."s1",BASICINFO."s2") ;
   
   复制

   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。

    <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>
   
   复制

1. 创建异步索引

   CREATE INDEX ASYNC_IDX ON SCHEMA_NAME.TABLE_NAME ( BASICINFO."s1", BASICINFO."s2" ) ASYNC;
   
   复制

2. 运行MapReduce

   执行MapReduce

   hbase org.apache.phoenix.mapreduce.index.IndexTool \
   --schema SCHEMA_NAME\
   --data-table TABLE_NAME\
   --index-table ASYNC_IDX \
   --output-path ASYNC_IDX_HFILES
   
   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=0\x0010\x00\xE4\xB8\x9A\xE4\xB8\xBB\x000\x000\x0010\x000\x00\xE6\xAD\xA3\xE5\xB8\xB8\xE4\xB8\x9A\xE4\xB8\xBB\x001001.99\x000\x001\x003\x00\xE8\x80\x81\xE5\xAE\xA2\xE6\x88\xB7\x00\xE6\x9C\xAA\xE7\x9F\xA5\x0042471415705946377 last=2\x009\x00\xE7\xA7\x9F\xE5\xAE\xA2\x002\x002\x009\x002\x00\xE9\x95\xBF\xE6\x9C\x9F\xE4\xB8\x8D\xE4\xBA\xA4\xE7\x89\xA9\xE4\xB8\x9A\xE7\xAE\xA1\xE7\x90\x86\xE8\xB4\xB9\x00988.56\x000\x001\x004\x00\xE6\x9C\xAA\xE7\x9F\xA5\x00\xE5\x9C\x9F\xE8\xB1\xAA\x0044ff3613003558171
   19/05/22 15:41:20 INFO index.IndexToolUtil:  Updated the status of the index INDEX_PERSONAS_TAG to ACTIVE
   
   复制

   遇到问题

   Error: Could not find or load main class org.apache.phoenix.mapreduce.index.IndexTool
   
   复制

   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
   
   复制

1. 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。

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：

create index my_index on my_table (v3);

复制

select v1 from my_table where v3 = '13406157616';

复制

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：

1. 使用覆盖索引

    CREATE INDEX cover_index ON my_table(v3) INCLUDE (v1);
   
   复制

   查看效果

    0: jdbc:phoenix:> select v1 from my_table where v3 = '13406157616';
    +------+
    |  V1  |
    +------+
    | 茹羽琦  |
    +------+
    1 row selected (0.01 seconds)
   
   复制

2. 使用 Hint 强制索引

    SELECT *+ INDEX(my_table my_index) */ v1 FROM my_table WHERE v3 = '13406157616';
   
   复制

   查看效果

    0: jdbc:phoenix:> SELECT *+ INDEX(my_table my_index) */ v1 FROM my_table WHERE v3 = '13406157616';
    +------+
    |  V1  |
    +------+
    | 茹羽琦  |
    +------+
    1 row selected (0.044 seconds)
   
   复制

3. 使用本地索引

    CREATE LOCAL INDEX local_index on my_table (v3);
   
   复制

   查看效果

    0: jdbc:phoenix:> select v1 from my_table where v3 = '13406157616';
    +------+
    |  V1  |
    +------+
    | 茹羽琦  |
    +------+
    1 row selected (0.025 seconds)
   
   复制