Hbase 学习(十一)使用hive往hbase当中导入数据

 我们可以有很多方式可以把数据导入到hbase当中,比如说用map-reduce,使用TableOutputFormat这个类,但是这种方式不是最优的方式。
  Bulk的方式直接生成HFiles,写入到文件系统当中,这种方式的效率很高。
  一般的步骤有两步
  (1)使用ImportTsv或者import工具或者自己写程序用hive/pig生成HFiles
  (2)用completebulkload把HFiles加载到hdfs上
  ImportTsv能把用Tab分隔的数据很方便的导入到hbase当中,但还有很多数据不是用Tab分隔的 下面我们介绍如何使用hive来导入数据到hbase当中。
  
  
  1.准备输入内容
  a.创建一个tables.ddl文件
  

-- pagecounts data comes from http://dumps.wikimedia.org/other/
pagecounts-raw/
-- documented http://www.mediawiki.org/wiki/Analytics/Wikistats
-- define an external table over raw pagecounts data
CREATE TABLE IF NOT EXISTS pagecounts (projectcode STRING, pagename
STRING, pageviews STRING, bytes STRING)
ROW FORMAT
DELIMITED FIELDS TERMINATED BY ' '
LINES TERMINATED BY '\n'
STORED AS TEXTFILE
LOCATION '/tmp/wikistats';
-- create a view, building a custom hbase rowkey
CREATE VIEW IF NOT EXISTS pgc (rowkey, pageviews, bytes) AS
SELECT concat_ws('/',
projectcode,
concat_ws('/',
pagename,
regexp_extract(INPUT__FILE__NAME, 'pagecounts-(\\d{8}-\\d{6})\
\..*$', 1))),
pageviews, bytes
FROM pagecounts;
-- create a table to hold the input split partitions
CREATE EXTERNAL TABLE IF NOT EXISTS hbase_splits(partition STRING)
ROW FORMAT
SERDE 'org.apache.hadoop.hive.serde2.binarysortable.
BinarySortableSerDe'
STORED AS
INPUTFORMAT 'org.apache.hadoop.mapred.TextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.
HiveNullValueSequenceFileOutputFormat'
LOCATION '/tmp/hbase_splits_out';
-- create a location to store the resulting HFiles
CREATE TABLE hbase_hfiles(rowkey STRING, pageviews STRING, bytes STRING)
STORED AS
INPUTFORMAT 'org.apache.hadoop.mapred.TextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.hbase.HiveHFileOutputFormat'
TBLPROPERTIES('hfile.family.path' = '/tmp/hbase_hfiles/w');
View Code
  b.创建HFils分隔文件,例子:sample.hql
  

-- prepate range partitioning of hfiles
ADD JAR /usr/lib/hive/lib/hive-contrib-0.11.0.1.3.0.0-104.jar;
SET mapred.reduce.tasks=1;
CREATE TEMPORARY FUNCTION row_seq AS 'org.apache.hadoop.hive.contrib.udf.
UDFRowSequence';
-- input file contains ~4mm records. Sample it so as to produce 5 input
splits.
INSERT OVERWRITE TABLE hbase_splits
SELECT rowkey FROM
(SELECT rowkey, row_seq() AS seq FROM pgc
TABLESAMPLE(BUCKET 1 OUT OF 10000 ON rowkey) s
ORDER BY rowkey
LIMIT 400) x
WHERE (seq % 100) = 0
ORDER BY rowkey
LIMIT 4;
-- after this is finished, combined the splits file:
dfs -cp /tmp/hbase_splits_out/* /tmp/hbase_splits;
View Code
  
  c.创建hfiles.hql
  

ADD JAR /usr/lib/hbase/hbase-0.94.6.1.3.0.0-104-security.jar;
ADD JAR /usr/lib/hive/lib/hive-hbase-handler-0.11.0.1.3.0.0-104.jar;
SET mapred.reduce.tasks=5;
SET hive.mapred.partitioner=org.apache.hadoop.mapred.lib.
TotalOrderPartitioner;
SET total.order.partitioner.path=/tmp/hbase_splits;
-- generate hfiles using the splits ranges
INSERT OVERWRITE TABLE hbase_hfiles
SELECT * FROM pgc
CLUSTER BY rowkey;
View Code
  
  2.导入数据
  注意:/$Path_to_Input_Files_on_Hive_Client是hive客户端的数据存储目录
  
mkdir /$Path_to_Input_Files_on_Hive_Client/wikistats
wget http://dumps.wikimedia.org/oth ... 8-10/
pagecounts-20081001-000000.gz
hadoop fs -mkdir /$Path_to_Input_Files_on_Hive_Client/wikistats
hadoop fs -put pagecounts-20081001-000000.
gz /$Path_to_Input_Files_on_Hive_Client/wikistats/

 
  3.创建必要的表
  注意:$HCATALOG_USER是HCatalog服务的用户(默认是hcat)
$HCATALOG_USER-f /$Path_to_Input_Files_on_Hive_Client/tables.ddl

  执行之后,我们会看到如下的提示:
  
OK
Time taken: 1.886 seconds
OK
Time taken: 0.654 seconds
OK
Time taken: 0.047 seconds
OK
Time taken: 0.115 seconds


  
  4.确认表已经正确创建
  执行以下语句
  
$HIVE_USER-e "select * from pagecounts limit 10;"

  
  执行之后,我们会看到如下的提示:
  
...
OK
aa Main_Page 4 41431
aa Special:ListUsers 1 5555
aa Special:Listusers 1 1052

  再执行
  
$HIVE_USER-e "select * from pgc limit 10;"

  执行之后,我们会看到如下的提示:
  
...
OK
aa/Main_Page/20081001-000000 4 41431
aa/Special:ListUsers/20081001-000000 1 5555
aa/Special:Listusers/20081001-000000 1 1052
...

  
  5.生成HFiles分隔文件
  
$HIVE_USER-f /$Path_to_Input_Files_on_Hive_Client/sample.hql
hadoop fs -ls /$Path_to_Input_Files_on_Hive_Client/hbase_splits

  
  为了确认,执行以下命令
hadoop jar /usr/lib/hadoop/contrib/streaming/hadoop-streaming-1.2.0.1.
3.0.0-104.jar -libjars /usr/lib/hive/lib/hive-exec-0.11.0.1.3.0.0-104.
jar -input /tmp/hbase_splits -output /tmp/hbase_splits_txt -inputformat
SequenceFileAsTextInputFormat

  执行之后,我们会看到如下的提示:
  
...
INFO streaming.StreamJob: Output: /tmp/hbase_splits_txt

  再执行这一句
  
hadoop fs -cat /tmp/hbase_splits_txt/*

  执行之后,我们会看到类似这样的结果
  
1 61 66 2e 71 2f 4d 61 69 6e 5f 50 61 67 65 2f 32 30 30 38 31 30 30 31 2d 30
30 30 30 30 30 00 (null)
01 61 66 2f 31 35 35 30 2f 32 30 30 38 31 30 30 31 2d 30 30 30 30 30 30 00
(null)
01 61 66 2f 32 38 5f 4d 61 61 72 74 2f 32 30 30 38 31 30 30 31 2d 30 30 30
30 30 30 00 (null)
01 61 66 2f 42 65 65 6c 64 3a 31 30 30 5f 31 38 33 30 2e 4a 50 47 2f 32 30
30 38 31 30 30 31 2d 30 30 30 30 30 30 00 (null)


  
  7.生成HFiles
HADOOP_CLASSPATH=/usr/lib/hbase/hbase-0.94.6.1.3.0.0-104-security.jar hive -f /$Path_to_Input_Files_on_Hive_Client/hfiles.hql

  
  以上内容是hdp的用户手册中推荐的方式,然后我顺便也从网上把最后的一步的命令格式给找出来了
  
hadoop jar hbase-VERSION.jar completebulkload /user/todd/myoutput mytable

 
  

0 个评论

要回复文章请先登录注册