Hive HBase Integration
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Avro Data Stored in HBase ColumnsAs of Hive 0.9.0 the HBase integration requires at least HBase 0.92, earlier versions of Hive were working with HBase 0.89/0.90 |
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Hive 1.x will remain compatible with HBase 0.98.x and lower versions. Hive 2.x will be compatible with HBase 1.x and higher. (See HIVE-10990 for details.) Consumers wanting to work with HBase 1.x using Hive 1.x will need to compile Hive 1.x stream code themselves. |
Introduction
This page documents the Hive/HBase integration support originally introduced in HIVE-705. This feature allows Hive QL statements to access HBase tables for both read (SELECT) and write (INSERT). It is even possible to combine access to HBase tables with native Hive tables via joins and unions.
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Here's an example using CLI from a source build environment, targeting a single-node HBase server. (Note that the jar locations and names have changed in Hive 0.9.0, so for earlier releases, some changes are needed.)
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$HIVE_SRC/build/dist/bin/hive --auxpath $HIVE_SRC/build/dist/lib/hive-hbase-handler-0.9.0.jar,$HIVE_SRC/build/dist/lib/hbase-0.92.0.jar,$HIVE_SRC/build/dist/lib/zookeeper-3.3.4.jar,$HIVE_SRC/build/dist/lib/guava-r09.jar --hiveconf hbase.master=hbase.yoyodyne.com:60000 |
Here's an example which instead targets a distributed HBase cluster where a quorum of 3 zookeepers is used to elect the HBase master:
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$HIVE_SRC/build/dist/bin/hive --auxpath $HIVE_SRC/build/dist/lib/hive-hbase-handler-0.9.0.jar,$HIVE_SRC/build/dist/lib/hbase-0.92.0.jar,$HIVE_SRC/build/dist/lib/zookeeper-3.3.4.jar,$HIVE_SRC/build/dist/lib/guava-r09.jar --hiveconf hbase.zookeeper.quorum=zk1.yoyodyne.com,zk2.yoyodyne.com,zk3.yoyodyne.com |
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In order to create a new HBase table which is to be managed by Hive, use the STORED BY
clause on CREATE TABLE
:
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CREATE TABLE hbase_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" = "xyz", "hbase.mapred.output.outputtable" = "xyz"); |
The hbase.columns.mapping
property is required and will be explained in the next section. The hbase.table.name
property is optional; it controls the name of the table as known by HBase, and allows the Hive table to have a different name. In this example, the table is known as hbase_table_1
within Hive, and as xyz
within HBase. If not specified, then the Hive and HBase and HBase table names will be identical. The hbase.mapred.output.outputtable
property is optional; it's needed if you plan to insert data to the table (the property is used by hbase.mapreduce.TableOutputFormat
)
After executing the command above, you should be able to see the new (empty) table in the HBase shell:
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$ hbase shell
HBase Shell; enter 'help<RETURN>' for list of supported commands.
Version: 0.20.3, r902334, Mon Jan 25 13:13:08 PST 2010
hbase(main):001:0> list
xyz
1 row(s) in 0.0530 seconds
hbase(main):002:0> describe "xyz"
DESCRIPTION ENABLED
{NAME => 'xyz', FAMILIES => [{NAME => 'cf1', COMPRESSION => 'NONE', VE true
RSIONS => '3', TTL => '2147483647', BLOCKSIZE => '65536', IN_MEMORY =>
'false', BLOCKCACHE => 'true'}]}
1 row(s) in 0.0220 seconds
hbase(main):003:0> scan "xyz"
ROW COLUMN+CELL
0 row(s) in 0.0060 seconds
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Here's how to move data from Hive into the HBase table (see GettingStarted for how to create the example table pokes
in Hive first):
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INSERT OVERWRITE TABLE hbase_table_1 SELECT * FROM pokes WHERE foo=98;
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Use HBase shell to verify that the data actually got loaded:
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hbase(main):009:0> scan "xyz"
ROW COLUMN+CELL
98 column=cf1:val, timestamp=1267737987733, value=val_98
1 row(s) in 0.0110 seconds
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And then query it back via Hive:
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hive> select * from hbase_table_1;
Total MapReduce jobs = 1
Launching Job 1 out of 1
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OK
98 val_98
Time taken: 4.582 seconds
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Inserting large amounts of data may be slow due to WAL overhead; if you would like to disable this, make sure you have HIVE-1383 (as of Hive 0.6), and then issue this command before the INSERT:
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set hive.hbase.wal.enabled=false;
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If you want to give Hive access to an existing HBase table, use CREATE EXTERNAL TABLE:
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CREATE EXTERNAL TABLE hbase_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" = "some_existing_table"); |
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, "hbase.mapred.output.outputtable" = "some_existing_table"); |
Again, hbase.columns.mapping
is required (columns.mapping is required (and will be validated against the existing HBase table's column families), whereas hbase.table.name
is optional. The hbase.mapred.output.outputtable
is optional.
Column Mapping
There are two SERDEPROPERTIES
that control the mapping of HBase columns to Hive:
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- for each Hive column, the table creator must specify a corresponding entry in the comma-delimited
hbase.columns.mapping
string (so for a Hive table with n columns, the string should have n entries); whitespace should not be used in between entries since these will be interperted as part of the column name, which is almost certainly not what you want - a mapping entry must be either
:key
,:timestamp
or of the formcolumn-family-name:[column-name][#(binary|string)
(the type specification that delimited by # was added in Hive 0.9.0, earlier versions interpreted everything as strings)- If no type specification is given the value from
hbase.table.default.storage.type
will be used - Any prefixes of the valid values are valid too (i.e.
#b
instead of#binary
) - If you specify a column as
binary
the bytes in the corresponding HBase cells are expected to be of the form that HBase'sBytes
class yields.
- If no type specification is given the value from
- there must be exactly one
:key
mapping (we don't support compound keys yetthis can be mapped either to a string or struct column–see Simple Composite Keys and Complex Composite Keys) - (note that before HIVE-1228 in Hive 0.6,
:key
was not supported, and the first Hive column implicitly mapped to the key; as of Hive 0.6, it is now strongly recommended that you always specify the key explictly; we will drop support for implicit key mapping in the future) - if no column-name is given, then the Hive column will map to all columns in the corresponding HBase column family, and the Hive MAP datatype must be used to allow access to these (possibly sparse) columns
- Since HBase 1.1 (HBASE-2828) there is currently no a way to access the HBase timestamp attribute , and queries always access data with the latest timestamp.Since HBase does not associate datatype information with columns, the serde converts everything to string representation before storing it in HBase; there is currently no way to plug in a custom serde per columnusing the special
:timestamp
mapping. It needs to be eitherbigint
ortimestamp
. - it is not necessary to reference every HBase column family, but those that are not mapped will be inaccessible via the Hive table; it's possible to map multiple Hive tables to the same HBase table
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Here's an example with three Hive columns and two HBase column families, with two of the Hive columns (value1
and value2
) corresponding to one of the column families (a
, with HBase column names b
and c
), and the other Hive column corresponding to a single column (e
) in its own column family (d
).
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CREATE TABLE hbase_table_1(key int, value1 string, value2 int, value3 int)
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES (
"hbase.columns.mapping" = ":key,a:b,a:c,d:e"
);
INSERT OVERWRITE TABLE hbase_table_1 SELECT foo, bar, foo+1, foo+2
FROM pokes WHERE foo=98 OR foo=100;
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Here's how this looks in HBase:
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hbase(main):014:0> describe "hbase_table_1"
DESCRIPTION ENABLED
{NAME => 'hbase_table_1', FAMILIES => [{NAME => 'a', COMPRESSION => 'N true
ONE', VERSIONS => '3', TTL => '2147483647', BLOCKSIZE => '65536', IN_M
EMORY => 'false', BLOCKCACHE => 'true'}, {NAME => 'd', COMPRESSION =>
'NONE', VERSIONS => '3', TTL => '2147483647', BLOCKSIZE => '65536', IN
_MEMORY => 'false', BLOCKCACHE => 'true'}]}
1 row(s) in 0.0170 seconds
hbase(main):015:0> scan "hbase_table_1"
ROW COLUMN+CELL
100 column=a:b, timestamp=1267740457648, value=val_100
100 column=a:c, timestamp=1267740457648, value=101
100 column=d:e, timestamp=1267740457648, value=102
98 column=a:b, timestamp=1267740457648, value=val_98
98 column=a:c, timestamp=1267740457648, value=99
98 column=d:e, timestamp=1267740457648, value=100
2 row(s) in 0.0240 seconds
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And when queried back into Hive:
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hive> select * from hbase_table_1;
Total MapReduce jobs = 1
Launching Job 1 out of 1
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OK
100 val_100 101 102
98 val_98 99 100
Time taken: 4.054 seconds
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Here's how a Hive MAP datatype can be used to access an entire column family. Each row can have a different set of columns, where the column names correspond to the map keys and the column values correspond to the map values.
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CREATE TABLE hbase_table_1(value map<string,int>, row_key int)
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES (
"hbase.columns.mapping" = "cf:,:key"
);
INSERT OVERWRITE TABLE hbase_table_1 SELECT map(bar, foo), foo FROM pokes
WHERE foo=98 OR foo=100;
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Here's how this looks in HBase (with different column names in different rows):
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hbase(main):012:0> scan "hbase_table_1"
ROW COLUMN+CELL
100 column=cf:val_100, timestamp=1267739509194, value=100
98 column=cf:val_98, timestamp=1267739509194, value=98
2 row(s) in 0.0080 seconds
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And when queried back into Hive:
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hive> select * from hbase_table_1;
Total MapReduce jobs = 1
Launching Job 1 out of 1
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OK
{"val_100":100} 100
{"val_98":98} 98
Time taken: 3.808 seconds
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Note that the key of the MAP must have datatype string, since it is used for naming the HBase column, so the following table definition will fail:
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CREATE TABLE hbase_table_1(key int, value map<int,int>)
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES (
"hbase.columns.mapping" = ":key,cf:"
);
FAILED: Error in metadata: java.lang.RuntimeException: MetaException(message:org.apache.hadoop.hive.serde2.SerDeException org.apache.hadoop.hive.hbase.HBaseSerDe: hbase column family 'cf:' should be mapped to map<string,?> but is mapped to map<int,int>)
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Hive
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MAP to HBase Column
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Prefix
Also note that starting with Hive 0.12, wildcards can also be used to retrieve columns. For instance, if you want to retrieve all columns in HBase that start with the prefix "col_prefix", a query like the following should workTable definitions such as the following are illegal because a
Hive column mapped to an entire column family must have MAP type:
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CREATE TABLE hbase_table_1(keyvalue intmap<string,int>, valuerow_key stringint) STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler' WITH SERDEPROPERTIES ( "hbase.columns.mapping" = "cf:keycol_prefix.*,cf:" ); FAILED: Error in metadata: java.lang.RuntimeException: MetaException(message:org.apache.hadoop.hive.serde2.SerDeException org.apache.hadoop.hive.hbase.HBaseSerDe: hbase column family 'cf:' should be mapped to map<string,?> but is mapped to string) |
Example with binary columns
Relying on the default value of hbase.table.default.storage.type
:
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CREATE TABLE hbase_table_1 (key int, value string, foobar double)
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES (
"hbase.columns.mapping" = ":key#b,cf:val,cf:foo#b"
);
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Specifying hbase.table.default.storage.type
:
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key"
);
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The same restrictions apply though. That is, the key of the map should be a string as it maps to the HBase column name and the value can be the type of value that you are retrieving. One other restriction is that all the values under the given prefix should be of the same type. That is, all of them should be of type "int" or type "string" and so on.
Hiding Column Prefixes
Starting with Hive 1.3.0, it is possible to hide column prefixes in select query results. There is the SerDe boolean property hbase.columns.mapping.prefix.hide (false by default), which defines if the prefix should be hidden in keys of Hive map:
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CREATE TABLE hbase_table_1(tags map<string,int>, row_key string)
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES (
"hbase.columns.mapping" = "cf:tag_.*,:key",
"hbase.columns.mapping.prefix.hide" = "true"
); |
Then a value of the column "tags" (select tags from hbase_table_1
) will be:
"x" : 1
instead of:
"tag_x" : 1
Illegal: Hive Primitive to HBase Column Family
Table definitions such as the following are illegal because a
Hive column mapped to an entire column family must have MAP type:
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CREATE TABLE hbase_table_1(key int, value string)
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES (
"hbase.columns.mapping" = ":key,cf:"
);
FAILED: Error in metadata: java.lang.RuntimeException: MetaException(message:org.apache.hadoop.hive.serde2.SerDeException org.apache.hadoop.hive.hbase.HBaseSerDe: hbase column family 'cf:' should be mapped to map<string,?> but is mapped to string)
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Example with Binary Columns
Relying on the default value of hbase.table.default.storage.type
:
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CREATE TABLE hbase_table_1 (key int, value string, foobar double)
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES (
"hbase.columns.mapping" = ":key#b,cf:val,cf:foo#b"
);
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Specifying hbase.table.default.storage.type
:
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CREATE TABLE hbase_table_1 (key int, value string, foobar double)
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES (
"hbase.columns.mapping" = ":key,cf:val#s,cf:foo",
"hbase.table.default.storage.type" = "binary"
);
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Simple Composite Row Keys
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As of Hive 0.13.0 |
Hive can read and write delimited composite keys to HBase by mapping the HBase row key to a Hive struct, and using ROW FORMAT DELIMITED...COLLECTION ITEMS TERMINATED BY. Example:
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-- Create a table with a composite row key consisting of two string fields, delimited by '~'
CREATE EXTERNAL TABLE delimited_example(key struct<f1:string, f2:string>, value string)
ROW FORMAT DELIMITED
COLLECTION ITEMS TERMINATED BY '~'
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES (
'hbase.columns.mapping'=':key,f:c1'); |
Complex Composite Row Keys and HBaseKeyFactory
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As of Hive 0.14.0 with HIVE-6411 (0.13.0 also supports complex composite keys, but using a different interface–see HIVE-2599 for that interface) |
For more complex use cases, Hive allows users to specify an HBaseKeyFactory which defines the mapping of a key to fields in a Hive struct. This can be configured using the property "hbase.composite.key.factory" in the SERDEPROPERTIES option:
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-- Parse a row key with 3 fixed width fields each of width 10
-- Example taken from: https://svn.apache.org/repos/asf/hive/trunk/hbase-handler/src/test/queries/positive/hbase_custom_key2.q
CREATE TABLE hbase_ck_4(key struct<col1:string,col2:string,col3:string>, value string)
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES (
"hbase.table.name" = "hbase_custom2",
"hbase.mapred.output.outputtable" = "hbase_custom2",
"hbase.columns.mapping" = ":key,cf:string",
"hbase.composite.key.factory"="org.apache.hadoop.hive.hbase.SampleHBaseKeyFactory2"); |
"hbase.composite.key.factory" should be the fully qualified class name of a class implementing HBaseKeyFactory. See SampleHBaseKeyFactory2 for a fixed length example in the same package. This class must be on your classpath in order for the above example to work. TODO: place these in an accessible place; they're currently only in test code.
Avro Data Stored in HBase Columns
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As of Hive 0.14.0 with HIVE-6147 |
Hive 0.14.0 onward supports storing and querying Avro objects in HBase columns by making them visible as structs to Hive. This allows Hive to perform ad hoc analysis of HBase data which can be deeply structured. Prior to 0.14.0, the HBase Hive integration only supported querying primitive data types in columns.
An example HiveQL statement where test_col_fam
is the column family and test_col
is the column name:
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CREATE EXTERNAL TABLE test_hbase_avro
ROW FORMAT SERDE 'org.apache.hadoop.hive.hbase.HBaseSerDe'
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES (
"hbase.columns.mapping" = ":key,test_col_fam:test_col",
"test_col_fam.test_col.serialization.type" = "avro",
"test_col_fam.test_col.avro.schema.url" = "hdfs://testcluster/tmp/schema.avsc")
TBLPROPERTIES (
"hbase.table.name" = "hbase_avro_table",
"hbase.mapred.output.outputtable" = "hbase_avro_table",
"hbase.struct.autogenerate"="true"); |
The important properties to note are the following three:
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"test_col_fam.test_col.serialization.type" = "avro" |
This property tells Hive that the given column under the given column family is an Avro column, so Hive needs to deserialize it accordingly.
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"test_col_fam.test_col.avro.schema.url" = "hdfs://testcluster/tmp/schema.avsc" |
Using this property you specify where the reader schema is for the column that will be used to deserialize. This can be on HDFS like mentioned here, or provided inline using something like "test_col_fam.test_col.avro.schema.literal"
property. If you have a custom store where you store this schema, you can write a custom implementation of AvroSchemaRetriever and plug that in using the "avro.schema.retriever property"
using a property like "test_col_fam.test_col.avro.schema.retriever"
. You would need to ensure that the jar with this custom class is on the Hive classpath. For a usage discussion and links to other resources, see HIVE-6147.
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"hbase.struct.autogenerate" = "true" |
Specifying this property lets Hive auto-deduce the columns and types using the schema that was provided. This allows you to avoid manually creating the columns and types for Avro schemas, which can be complicated and deeply nested.
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Put Timestamps
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As of Hive 0.9.0 |
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For example, the pokes table contains rows with duplicate keys. If it is copied into another Hive table, the duplicates are preserved:
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CREATE TABLE pokes2(foo INT, bar STRING);
INSERT OVERWRITE TABLE pokes2 SELECT * FROM pokes;
-- this will return 3
SELECT COUNT(1) FROM POKES WHERE foo=498;
-- this will also return 3
SELECT COUNT(1) FROM pokes2 WHERE foo=498;
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But in HBase, the duplicates are silently eliminated:
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CREATE TABLE pokes3(foo INT, bar STRING)
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES (
"hbase.columns.mapping" = ":key,cf:bar"
);
INSERT OVERWRITE TABLE pokes3 SELECT * FROM pokes;
-- this will return 1 instead of 3
SELECT COUNT(1) FROM pokes3 WHERE foo=498;
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The QL tests can be executed via ant like this:
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ant test -Dtestcase=TestHBaseCliDriver -Dqfile=hbase_queries.q
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- Primary credit for this feature goes to Samuel Guo, who did most of the development work in the early drafts of the patch
Open Issues (JIRA)
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