Getting Started with Hive and MapR Database Integration

In this tutorial we will:

  • Create a Hive table
  • Populate the Hive table with data from a text file
  • Query the Hive table
  • Create a Hive-MapR Database table
  • Introspect the Hive-MapR Database table from the HBase shell
  • Populate the Hive-MapR Database table with data from the Hive table
  • Query the Hive-MapR Database table from Hive
  • Convert an existing MapR Database table into a Hive-MapR table

Be sure that you have successfully completed all of the steps in Installing Hive and review the MapR Database topics before beginning this Getting Started tutorial.

This Getting Started tutorial is based on the Hive-HBase Integration section of the Apache Hive Wiki. However, please note that there are some significant differences.

Create a Hive table with two columns

Change to your Hive installation directory if you're not already there and start Hive:

$ cd $HIVE_HOME
$ bin/hive

Execute the CREATE TABLE command to create the Hive pokes table

hive> CREATE TABLE pokes (foo INT, bar STRING);

To see if the pokes table has been created successfully, execute the SHOW TABLES command

hive> SHOW TABLES;
OK
pokes
Time taken: 0.74 seconds

The pokes table appears in the list of tables. Populate the Hive pokes table with data:

The kv1.txt file is provided in the $HIVE_HOME/examples/files directory. Execute the LOAD DATA LOCAL INPATH command to populate the Hive pokes table with data from the kv1.txt file.

hive> LOAD DATA LOCAL INPATH './examples/files/kv1.txt' OVERWRITE INTO TABLE pokes;

A message appears confirming that the table was created successfully, and the Hive prompt reappears:

Copying data from file:
...
OK
Time taken: 0.278 seconds
hive>

Execute a SELECT query on the Hive pokes table

hive> SELECT * FROM pokes WHERE foo = 98;

The SELECT statement executes, runs a MapReduce application, and prints the application output:

OK
98      val_98
98      val_98
Time taken: 18.059 seconds

The output of the SELECT command displays two identical rows because there are two identical rows in the Hive pokes table with a key of 98.

Warning:

Hive tables can have multiple identical keys. As we will see shortly, MapR Database tables cannot have multiple identical keys, only unique keys.

Create a Hive-MapR Database table

Enter these four lines of code at the Hive prompt:

hive> CREATE TABLE mapr_table_1(key int, value string)
    > STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
    > WITH SERDEPROPERTIES ("hbase.columns.mapping" = ":key,cf1:val")
    > TBLPROPERTIES ("hbase.table.name" = "/user/mapr/xyz");

After a brief delay, a message appears confirming that the table was created successfully:

OK
Time taken: 5.195 seconds

Note: The TBLPROPERTIES command is not required, but those new to Hive-MapR Database integration may find it easier to understand what's going on if Hive and MapR Database use different names for the same table.

In this example, Hive will recognize this table as "mapr_table_1" and MapR Database will recognize this table as "xyz".

Start the HBase shell

Keeping the Hive terminal session open, start a new terminal session for HBase, then start the HBase shell:

$ cd $HBASE_HOME
$ bin/hbase shell
HBase Shell; enter 'help<RETURN>' for list of supported commands.
Type "exit<RETURN>" to leave the HBase Shell
Version 0.90.4, rUnknown, Wed Nov  9 17:35:00 PST 2011

hbase(main):001:0>

Execute the list command to see a list of HBase tables

hbase(main):001:0> list
TABLE
/user/mapr/xyz
1 row(s) in 0.8260 seconds

HBase recognizes the Hive-MapR Database table named xyz in directory /user/mapr. This is the same table known to Hive as mapr_table_1.

Display the description of the /user/mapr/xyz table in the HBase shell

hbase(main):004:0> describe "/user/mapr/xyz"
DESCRIPTION                                          ENABLED
 {NAME => '/user/mapr/xyz', FAMILIES => [{NAME => 'cf1', DATA_B true
 LOCK_ENCODING => 'NONE', BLOOMFILTER => 'NONE', REP
 LICATION_SCOPE => '0', VERSIONS => '3', MIN_VERSION
 S => '0', TTL => '2147483647', KEEP_DELETED_CELLS =
 > 'false', BLOCKSIZE => '65536', IN_MEMORY => 'fals
 e', ENCODE_ON_DISK => 'true', BLOCKCACHE => 'true'}
 ]}
1 row(s) in 0.0240 seconds

From the Hive prompt, insert data from the Hive table pokes into the Hive-MapR Database table mapr_table_1

hive> INSERT OVERWRITE TABLE mapr_table_1 SELECT * FROM pokes WHERE foo=98;
...
2 Rows loaded to mapr_table_1
OK
Time taken: 13.384 seconds

Query mapr_table_1 to see the data we have inserted into the Hive-MapR Database table

hive> SELECT * FROM mapr_table_1;
OK
98      val_98
Time taken: 0.56 seconds

Even though we loaded two rows from the Hive pokes table that had the same key of 98, only one row was actually inserted into mapr_table_1. This is because mapr_table_1 is a MapR Database table, and although Hive tables support duplicate keys, MapR Database tables only support unique keys. MapR Database tables arbitrarily retain only one key, and silently discard all of the data associated with duplicate keys.

Convert a pre-existing MapR Database table to a Hive-MapR Database table

To convert a pre-existing MapR Database table to a Hive-MapR Database table, enter the following four commands at the Hive prompt.

Note that in this example the existing MapR Database table is my_mapr_table in directory /user/mapr.

hive> CREATE EXTERNAL TABLE mapr_table_2(key int, value string)
    > STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
    > WITH SERDEPROPERTIES ("hbase.columns.mapping" = "cf1:val")
    > TBLPROPERTIES("hbase.table.name" = "/user/mapr/my_mapr_table");

Now we can run a Hive query against the pre-existing MapR Database table /user/mapr/my_mapr_table that Hive sees as mapr_table_2:

hive> SELECT * FROM mapr_table_2 WHERE key > 400 AND key < 410;
Total MapReduce jobs = 1
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
...
OK
401     val_401
402     val_402
403     val_403
404     val_404
406     val_406
407     val_407
409     val_409
Time taken: 9.452 seconds