Hive索引
一、Hive Index具体实现
索引是标准的数据库技术，hive 0.7版本之后支持索引。hive索引采用的不是'one size fites all'的索引实现方式，而是提供插入式接口，并且提供一个具体的索引实现作为参考。Hive的Index接口如下：
/** * HiveIndexHandler defines a pluggable interface for adding new index handlers * to Hive. */public interface HiveIndexHandler extends Configurable { /** * Determines whether this handler implements indexes by creating an index * table. * * @return true if index creation implies creation of an index table in Hive; * false if the index representation is not stored in a Hive table */ boolean usesIndexTable(); /** * Requests that the handler validate an index definition and fill in * additional information about its stored representation. * * @param baseTable * the definition of the table being indexed * * @param index * the definition of the index being created * * @param indexTable * a partial definition of the index table to be used for storing the * index representation, or null if usesIndexTable() returns false; * the handler can augment the index's storage descriptor (e.g. with * information about input/output format) and/or the index table's * definition (typically with additional columns containing the index * representation, e.g. pointers into HDFS). * * @throws HiveException if the index definition is invalid with respect to * either the base table or the supplied index table definition */ void analyzeIndexDefinition( org.apache.hadoop.hive.metastore.api.Table baseTable, org.apache.hadoop.hive.metastore.api.Index index, org.apache.hadoop.hive.metastore.api.Table indexTable) throws HiveException; /** * Requests that the handler generate a plan for building the index; the plan * should read the base table and write out the index representation. * * @param baseTbl * the definition of the table being indexed * * @param index * the definition of the index * * @param baseTblPartitions * list of base table partitions with each element mirrors to the * corresponding one in indexTblPartitions * * @param indexTbl * the definition of the index table, or null if usesIndexTable() * returns null * * @param inputs * inputs for hooks, supplemental outputs going * along with the return value * * @param outputs * outputs for hooks, supplemental outputs going * along with the return value * * @return list of tasks to be executed in parallel for building the index * * @throws HiveException if plan generation fails */ List<Task<?>> generateIndexBuildTaskList( org.apache.hadoop.hive.ql.metadata.Table baseTbl, org.apache.hadoop.hive.metastore.api.Index index, List<Partition> indexTblPartitions, List<Partition> baseTblPartitions, org.apache.hadoop.hive.ql.metadata.Table indexTbl, Set<ReadEntity> inputs, Set<WriteEntity> outputs) throws HiveException; /** * Generate the list of tasks required to run an index optimized sub-query for the * given predicate, using the given indexes. If multiple indexes are * provided, it is up to the handler whether to use none, one, some or all of * them. The supplied predicate may reference any of the columns from any of * the indexes. If the handler decides to use more than one index, it is * responsible for generating tasks to combine their search results * (e.g. performing a JOIN on the result). * @param indexes * @param predicate * @param pctx * @param queryContext contains results, such as query tasks and input configuration */ void generateIndexQuery(List<Index> indexes, ExprNodeDesc predicate, ParseContext pctx, HiveIndexQueryContext queryContext); /** * Check the size of an input query to make sure it fits within the bounds * * @param inputSize size (in bytes) of the query in question * @param conf * @return true if query is within the bounds */ boolean checkQuerySize(long inputSize, HiveConf conf);}创建索引的时候，Hive首先调用接口的usesIndexTable方法，判断索引是否是已Hive Table的方式存储（默认的实现是存储在Hive中的）。然后调用analyzeIndexDefinition分析索引创建语句是否合法，如果没有问题将在元数据标IDXS中添加索引表，否则抛出异常。如果索引创建语句中使用with deferred rebuild，在执行alter index xxx_index on xxx rebuild时将调用generateIndexBuildTaskList获取Index的MapReduce，并执行为索引填充数据。
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测试索引例子：
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1.创建测试数据
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#! /bin/bash #generating 350M raw data. i=0 while [ $i -ne 1000000 ] do echo -e "$i\tA decade ago, many were predicting that Cooke, a New York City prodigy, would become a basketball shoe pitchman and would flaunt his wares and skills at All-Star weekends like the recent aerial show in Orlando, Fla. There was a time, however fleeting, when he was more heralded, or perhaps merely hyped, than any other high school player in America." i=$(($i+1)) done?
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2.创建测试表1
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create table table01( id int, name string) ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t';?
load data local inpath '/data/tmp/huzhirong/dual.txt' overwrite into table table01;?
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3.创建测试表2，并从表1中select数据
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create table table02 as select id,name as text from table01;?table02在hdfs的数据
hive> dfs -ls /user/hive/warehouse/table02; Found 5 items-rw-r--r-- 3 hadoop supergroup 88453176 2013-04-26 20:56 /user/hive/warehouse/table02/000000_0-rw-r--r-- 3 hadoop supergroup 67108860 2013-04-26 20:56 /user/hive/warehouse/table02/000001_0-rw-r--r-- 3 hadoop supergroup 67109134 2013-04-26 20:56 /user/hive/warehouse/table02/000002_0-rw-r--r-- 3 hadoop supergroup 67108860 2013-04-26 20:56 /user/hive/warehouse/table02/000003_0-rw-r--r-- 3 hadoop supergroup 67108860 2013-04-26 20:56 /user/hive/warehouse/table02/000004_0?测试查询：
select * from table02 where id=500000;?耗时：
OK500000 A decade ago, many were predicting that Cooke, a New York City prodigy, would become a basketball shoe pitchman and would flaunt his wares and skills at All-Star weekends like the recent aerial show in Orlando, Fla. There was a time, however fleeting, when he was more heralded, or perhaps merely hyped, than any other high school player in America.Time taken: 35.022 seconds
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4.创建索引
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create index table02_index on table table02(id) as 'org.apache.hadoop.hive.ql.index.compact.CompactIndexHandler' with deferred rebuild;
alter index table02_index on table02 rebuild;
Loading data to table default.default__table02_table02_index__Moved to trash: hdfs://namenode.hadoop.game.yy.com/user/hive/warehouse/default__table02_table02_index__Table default.default__table02_table02_index__ stats: [num_partitions: 0, num_files: 1, num_rows: 0, total_size: 87733114, raw_data_size: 0]MapReduce Jobs Launched: Job 0: Map: 3 Reduce: 1 Cumulative CPU: 51.28 sec HDFS Read: 357021261 HDFS Write: 87733114 SUCCESSTotal MapReduce CPU Time Spent: 51 seconds 280 msecOKTime taken: 65.6 seconds
hive> dfs -ls /user/hive/warehouse/default__table02_table02_index__;Found 1 items-rw-r--r-- 3 hadoop supergroup 87733114 2013-04-26 21:04 /user/hive/warehouse/default__table02_table02_index__/000000_0?可以看到索引内存储的数据：
hive> select * from default__table02_table02_index__ limit 3;OK0 hdfs://namenode.hadoop.game.yy.com/user/hive/warehouse/table02/000002_0 [0]1 hdfs://namenode.hadoop.game.yy.com/user/hive/warehouse/table02/000002_0 [352]2 hdfs://namenode.hadoop.game.yy.com/user/hive/warehouse/table02/000002_0 [704]?应该是{值，HDFS文件位置，偏移量的数组（可能有多个）}自定义索引文件：
insert overwrite directory "/tmp/table02_index_data" select `_bucketname`, `_offsets` from default__table02_table02_index__ where id =500000;?查询table02数据直接查询：
hive> select * from table02 where id =500000;Total MapReduce jobs = 1Launching Job 1 out of 1Number of reduce tasks is set to 0 since there's no reduce operatorStarting Job = job_201301301559_29049, Tracking URL = http://namenode.hadoop.game.yy.com:50030/jobdetails.jsp?jobid=job_201301301559_29049Kill Command = /home/hadoop/hadoop-1.0.3/libexec/../bin/hadoop job -Dmapred.job.tracker=namenode.hadoop.game.yy.com:8021 -kill job_201301301559_29049Hadoop job information for Stage-1: number of mappers: 6; number of reducers: 02013-04-26 22:34:20,755 Stage-1 map = 0%, reduce = 0%2013-04-26 22:34:26,797 Stage-1 map = 17%, reduce = 0%, Cumulative CPU 2.23 sec2013-04-26 22:34:27,812 Stage-1 map = 17%, reduce = 0%, Cumulative CPU 2.23 sec2013-04-26 22:34:28,859 Stage-1 map = 17%, reduce = 0%, Cumulative CPU 2.23 sec2013-04-26 22:34:29,871 Stage-1 map = 17%, reduce = 0%, Cumulative CPU 2.23 sec2013-04-26 22:34:30,874 Stage-1 map = 17%, reduce = 0%, Cumulative CPU 2.23 sec2013-04-26 22:34:31,877 Stage-1 map = 17%, reduce = 0%, Cumulative CPU 2.23 sec2013-04-26 22:34:32,879 Stage-1 map = 83%, reduce = 0%, Cumulative CPU 11.58 sec2013-04-26 22:34:33,882 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 12.99 sec2013-04-26 22:34:34,884 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 12.99 sec2013-04-26 22:34:35,887 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 12.99 sec2013-04-26 22:34:36,890 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 12.99 sec2013-04-26 22:34:37,893 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 12.99 sec2013-04-26 22:34:38,895 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 12.99 sec2013-04-26 22:34:39,898 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 12.99 secMapReduce Total cumulative CPU time: 12 seconds 990 msecEnded Job = job_201301301559_29049MapReduce Jobs Launched: Job 0: Map: 6 Cumulative CPU: 12.99 sec HDFS Read: 357021325 HDFS Write: 357 SUCCESSTotal MapReduce CPU Time Spent: 12 seconds 990 msecOK500000 A decade ago, many were predicting that Cooke, a New York City prodigy, would become a basketball shoe pitchman and would flaunt his wares and skills at All-Star weekends like the recent aerial show in Orlando, Fla. There was a time, however fleeting, when he was more heralded, or perhaps merely hyped, than any other high school player in America.Time taken: 33.189 seconds?指定索引：
hive> set hive.index.compact.file=/tmp/table02_index_data; hive> set hive.optimize.index.filter=false; hive> set hive.input.format=org.apache.hadoop.hive.ql.index.compact.HiveCompactIndexInputFormat;hive> select * from table02 where id =500000; Total MapReduce jobs = 1Launching Job 1 out of 1Number of reduce tasks is set to 0 since there's no reduce operatorStarting Job = job_201301301559_29051, Tracking URL = http://namenode.hadoop.game.yy.com:50030/jobdetails.jsp?jobid=job_201301301559_29051Kill Command = /home/hadoop/hadoop-1.0.3/libexec/../bin/hadoop job -Dmapred.job.tracker=namenode.hadoop.game.yy.com:8021 -kill job_201301301559_29051Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 02013-04-26 22:40:06,793 Stage-1 map = 0%, reduce = 0%2013-04-26 22:40:12,803 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.69 sec2013-04-26 22:40:13,806 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.69 sec2013-04-26 22:40:14,808 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.69 sec2013-04-26 22:40:15,811 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.69 sec2013-04-26 22:40:16,813 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.69 sec2013-04-26 22:40:17,815 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.69 sec2013-04-26 22:40:18,818 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 1.69 secMapReduce Total cumulative CPU time: 1 seconds 690 msecEnded Job = job_201301301559_29051MapReduce Jobs Launched: Job 0: Map: 1 Cumulative CPU: 1.69 sec HDFS Read: 33554658 HDFS Write: 357 SUCCESSTotal MapReduce CPU Time Spent: 1 seconds 690 msecOK500000 A decade ago, many were predicting that Cooke, a New York City prodigy, would become a basketball shoe pitchman and would flaunt his wares and skills at All-Star weekends like the recent aerial show in Orlando, Fla. There was a time, however fleeting, when he was more heralded, or perhaps merely hyped, than any other high school player in America.Time taken: 26.776 seconds?看Map数：变成1个了，不过这里是手工插入id=500000的索引。总结：索引表的基本包含几列：1. 源表的索引列；2. _bucketname hdfs中文件地址 3. 索引列在hdfs文件中的偏移量。原理是通过记录索引列在HDFS中的偏移量，精准获取数据，避免全表扫描。