Hive中視圖機制的初步使用及分析

作者: 大圓那些事 | 文章可以轉載，請以超鏈接形式標明文章原始出處和作者信息

網址: http://www.cnblogs.com/panfeng412/archive/2013/04/29/hive-view-usage-and-analysis.html

本文是對Hive中邏輯視圖的介紹，通過一個簡單的視圖例子，說明其使用方法及執行過程。

Hive 0.6版本及以上支持視圖（View，詳見Hive的RELEASE_NOTES.txt），Hive View具有以下特點：

1）View是邏輯視圖，暫不支持物化視圖（后續將在1.0.3版本以后支持）；

2）View是只讀的，不支持LOAD/INSERT/ALTER。需要改變View定義，可以是用Alter View；

3）View內可能包含ORDER BY/LIMIT語句，假如一個針對View的查詢也包含這些語句， 則View中的語句優先級高；

4）支持迭代View。

CDH4中自帶的Hive版本為0.10.0，支持的View是邏輯視圖，因此本質上來說View只是為了使用上的方便，從執行效率上來說沒有區別，甚至可能因為要多一次對MetaStore元數據的操作效率略有下降（這里只是一種理論上的推測，實際可能看不出太大區別）。

下面是簡單的驗證過程（感興趣的可以看下，以下過程如有問題，可以一起交流）：

1）創建一個測試表：

hive> create table test (id int, name string);
OK
Time taken: 0.19 seconds
hive> desc test;                                                                           
OK
id      int
name    string
Time taken: 0.16 seconds

2）創建一個View之前，使用explain命令查看創建View的命令是如何被Hive解釋執行的：

hive> explain create view test_view (id, name_length) as  select id, length(name) from test;
OK
ABSTRACT SYNTAX TREE:
  (TOK_CREATEVIEW (TOK_TABNAME test_view) (TOK_TABCOLNAME (TOK_TABCOL id TOK_NULL) (TOK_TABCOL name_length TOK_NULL)) (TOK_QUERY (TOK_FROM (TOK_TABREF (TOK_TABNAME test))) (TOK_INSERT (TOK_DESTINATION (TOK_DIR TOK_TMP_FILE)) (TOK_SELECT (TOK_SELEXPR (TOK_TABLE_OR_COL id)) (TOK_SELEXPR (TOK_FUNCTION length (TOK_TABLE_OR_COL name)))))))
STAGE DEPENDENCIES:
  Stage-0 is a root stage
STAGE PLANS:
  Stage: Stage-0
      Create View Operator:
        Create View
          if not exists: false
          or replace: false
          columns: id int, name_length int
          expanded text: SELECT `id` AS `id`, `_c1` AS `name_length` FROM (select `test`.`id`, length(`test`.`name`) from `default`.`test`) `test_view`
          name: test_view
          original text: select id, length(name) from test
Time taken: 0.088 seconds

可見，創建View的過程解釋后並沒有實際執行Map Reduce的Stage，只包含一個Create View Operator的Stage，這個階段只是對MySQL MetaStore進行元數據操作，記錄View的相關元數據而已。

3）接下來，實際創建這個View：

hive> create view test_view (id, name_length) as  select id, length(name) from test;   
OK
Time taken: 0.1 seconds

4）執行這個View之前，先explain查看實際被翻譯后的執行過程：

hive> explain select name_length from test_view;
OK
ABSTRACT SYNTAX TREE:
  (TOK_QUERY (TOK_FROM (TOK_TABREF (TOK_TABNAME test_view))) (TOK_INSERT (TOK_DESTINATION (TOK_DIR TOK_TMP_FILE)) (TOK_SELECT (TOK_SELEXPR (TOK_TABLE_OR_COL name_length)))))
STAGE DEPENDENCIES:
  Stage-1 is a root stage
  Stage-0 is a root stage
STAGE PLANS:
  Stage: Stage-1
    Map Reduce
      Alias -> Map Operator Tree:
        test_view:test_view:test
          TableScan
            alias: test
            Select Operator
              expressions:
                    expr: length(name)
                    type: int
              outputColumnNames: _col1
              Select Operator
                expressions:
                      expr: _col1
                      type: int
                outputColumnNames: _col1
                Select Operator
                  expressions:
                        expr: _col1
                        type: int
                  outputColumnNames: _col0
                  File Output Operator
                    compressed: false
                    GlobalTableId: 0
                    table:
                        input format: org.apache.hadoop.mapred.TextInputFormat
                        output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
  Stage: Stage-0
    Fetch Operator
      limit: -1
Time taken: 0.107 seconds

可以看出，對View進行的查找過程，實際還是對原始test表進行的查詢操作（分為Stage-0和Stage-1兩個階段）。

5）最后，實際對這個View執行一次查詢，顯示Stage-1階段對原始表test進行了MapReduce過程：

hive> select name_length from test_view;       
Total MapReduce jobs = 1
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_201303092253_0057, Tracking URL = http://jobtracker.host:50030/jobdetails.jsp?jobid=job_201303092253_0057
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_201303092253_0057
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0
2013-03-13 22:43:39,044 Stage-1 map = 0%,  reduce = 0%
2013-03-13 22:43:42,074 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 0.73 sec
2013-03-13 22:43:43,086 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 0.73 sec
2013-03-13 22:43:44,098 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 0.73 sec
2013-03-13 22:43:45,113 Stage-1 map = 100%,  reduce = 100%, Cumulative CPU 0.73 sec
MapReduce Total cumulative CPU time: 730 msec
Ended Job = job_201303092253_0057
MapReduce Jobs Launched:
Job 0: Map: 1   Cumulative CPU: 0.73 sec   HDFS Read: 250 HDFS Write: 0 SUCCESS
Total MapReduce CPU Time Spent: 730 msec
OK
Time taken: 15.793 seconds