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The editor today takes you to understand the application example analysis of big data HIve data warehouse. The knowledge points in the article are introduced in great detail. Friends who feel helpful can browse the content of the article together with the editor, hoping to help more friends who want to solve this problem to find the answer to the problem. Let's go deep into the knowledge of "big data HIve data Warehouse Application case Analysis" with the editor.

Now, big data's big wave has involved every one of us, and along with big data's technology, HIve data warehouse has attracted public attention. As one of the core tools of big data analysis, it has been playing an important role in providing decision support for enterprises. Therefore, mastering Hive is one of the keys to getting started with big data. Let's take a look at the HIve data warehouse application case.

Load local file data into the Hive data warehouse:

First create a text file under / public/users/yexin/Hadoop/hadoopdata:

There are only two ways to load data after a table is established in Hive:

(1) load data from the local file system

(2) load data from the Hadoop file system

Start the hive service on the node63 node: enter: hive-- service metastore &; hive-- service hiveserver2 or direct input

Enter hiveserver2

Enter hive to log in under the node70 node and do the following

Create a table:

Hive > CREATE TABLE score (

> sno int,name String

> java decimal (10jue 2)

> python decimal (10jue 2)

> ROW FORMAT DELIMITED

> FIELDS TERMINATED BY'\ t'

> LINES TERMINATED BY'\ n'

> STORED AS TEXTFILE

OK

Time taken: 0.429 seconds

Import data: import by from local system file

Time taken: 0.429 seconds

Hive > load data local inpath'/ public/users/yexin/Hadoop/hadoopdata/score.txt' overwrite into table

Score

Loading data to table yexin.score

OK

Time taken: 1.413 seconds

Query score table:

View HDFS data:

View metadata:

Use hive

Delete table: drop tabel score? Remember that when you delete the table, the data on the HDFS is deleted together.

Note: if an external table is created, the files in the HDFS after drop are not deleted

Beelin command:

Set access permissions: modify the core-site.xml of hadoop

Using other nodes as clients, you need to configure the hive2 listener node port on the node63 node to allow remote access to the hive service (beeline)

Vim hive-site.xml

Add: to bind node70 client access. So that it can be accessed remotely.

Hive.server2.thrift.bind.host

Node70

Hive.server2.long.polling.timeout

5000

Connect to HiveServer2 at the node70 node (the client of hive) (allowing multiple clients to operate concurrently)

Enter: beeline to enter beeline, enter:

! connect jdbc:hive2://node70:10000 yexin 12345

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