Interesting point below:

 

Well you use a text format for your data so you should not be surprised. For 
text based formats, such as csv, you can always use the hive bitmap index.

 

 

How can one create a bitmap index in Hive please?

 

 

Dr Mich Talebzadeh

 

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From: Jörn Franke [mailto:jornfra...@gmail.com] 
Sent: 08 January 2016 08:49
To: user@hive.apache.org
Subject: Re: Impact of partitioning on certain queries

 

Well you use a text format for your data so you should not be surprised. For 
text based formats, such as csv, you can always use the hive bitmap index. I do 
not think it makes a lot of sense to compare here processing csv files and 
internal tables of a relational database.


On 08 Jan 2016, at 09:30, Mich Talebzadeh <m...@peridale.co.uk 
<mailto:m...@peridale.co.uk> > wrote:

Well that is debatable.

 

The following table sales is partitioned in Oracle but has local bitmap indexes 
that help the query.

 

select * from sales where prod_id = 10;

 

no rows selected

 

 

Execution Plan

----------------------------------------------------------

Plan hash value: 511273406

 

---------------------------------------------------------------------------------------------------------------------

| Id  | Operation                          | Name           | Rows  | Bytes | 
Cost (%CPU)| Time     | Pstart| Pstop |

---------------------------------------------------------------------------------------------------------------------

|   0 | SELECT STATEMENT                   |                |   347 | 10063 |   
 93   (0)| 00:00:02 |       |       |

|   1 |  PARTITION RANGE ALL               |                |   347 | 10063 |   
 93   (0)| 00:00:02 |     1 |    28 |

|   2 |   TABLE ACCESS BY LOCAL INDEX ROWID| SALES          |   347 | 10063 |   
 93   (0)| 00:00:02 |     1 |    28 |

|   3 |    BITMAP CONVERSION TO ROWIDS     |                |       |       |   
         |          |       |       |

|*  4 |     BITMAP INDEX SINGLE VALUE      | SALES_PROD_BIX |       |       |   
         |          |     1 |    28 |

---------------------------------------------------------------------------------------------------------------------

 

Obviously at this stage we do not have local indexes in Hive. That could make 
it moredefficient for search and IMO will be a great tool.

 

Cheers,

 

 

Dr Mich Talebzadeh

 

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From: Jörn Franke [mailto:jornfra...@gmail.com] 
Sent: 08 January 2016 06:20
To: user@hive.apache.org <mailto:user@hive.apache.org> 
Subject: Re: Impact of partitioning on certain queries

 

This observation is correct and it is the same  behavior as you see it in other 
databases supporting partitions. Usually you should avoid many small partitions.


On 07 Jan 2016, at 23:53, Mich Talebzadeh <m...@peridale.co.uk 
<mailto:m...@peridale.co.uk> > wrote:

Ok we hope that partitioning improves performance where the predicate is on 
partitioned columns

 

I have two tables. One a basic table called smallsales defined as below

 

CREATE TABLE `smallsales`(                                              |

|   `prod_id` bigint,                                                     |

|   `cust_id` bigint,                                                     |

|   `time_id` timestamp,                                                  |

|   `channel_id` bigint,                                                  |

|   `promo_id` bigint,                                                    |

|   `quantity_sold` decimal(10,0),                                        |

|   `amount_sold` decimal(10,0))                                          |

| ROW FORMAT SERDE                                                        |

|   'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe'                  |

| STORED AS INPUTFORMAT                                                   |

|   'org.apache.hadoop.mapred.TextInputFormat'                            |

| OUTPUTFORMAT                                                            |

|   'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'          |

| LOCATION                                                                |

|   'hdfs://rhes564:9000/user/hive/warehouse/oraclehadoop.db/smallsales'  |

| TBLPROPERTIES (                                                         |

|   'COLUMN_STATS_ACCURATE'='true',                                       |

|   'last_modified_by'='hduser',                                          |

|   'last_modified_time'='1451644705',                                    |

|   'numFiles'='1',                                                       |

|   'numRows'='5000000',                                                  |

|   'rawDataSize'='193437457',                                            |

|   'totalSize'='198437457',                                              |

|   'transient_lastDdlTime'='1451784743')                                 |

+-------------------------------------------------------------------------+--+

 

 

So 5 million rows.

 

 

I then created a partitioned table called sales as below

 

|                                createtab_stmt                                 
|

+-------------------------------------------------------------------------------+--+

| CREATE TABLE `sales`(                                                         
|

|   `prod_id` bigint,                                                           
|

|   `cust_id` bigint,                                                           
|

|   `time_id` timestamp,                                                        
|

|   `channel_id` bigint,                                                        
|

|   `promo_id` bigint,                                                          
|

|   `quantity_sold` decimal(10,0),                                              
|

|   `amount_sold` decimal(10,0))                                                
|

| PARTITIONED BY (                                                              
|

|   `year` int,                                                                 
|

|   `month` int)                                                                
|

| CLUSTERED BY (                                                                
|

|   prod_id,                                                                    
|

|   cust_id,                                                                    
|

|   time_id,                                                                    
|

|   channel_id,                                                                 
|

|   promo_id)                                                                   
|

| INTO 256 BUCKETS                                                              
|

| ROW FORMAT SERDE                                                              
|

|   'org.apache.hadoop.hive.ql.io.orc.OrcSerde'                                 
|

| STORED AS INPUTFORMAT                                                         
|

|   'org.apache.hadoop.hive.ql.io.orc.OrcInputFormat'                           
|

| OUTPUTFORMAT                                                                  
|

|   'org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat'                          
|

| LOCATION                                                                      
|

|   'hdfs://rhes564:9000/user/hive/warehouse/oraclehadoop.db/sales'             
|

| TBLPROPERTIES (                                                               
|

|   'orc.bloom.filter.columns'='PROD_ID,CUST_ID,TIME_ID,CHANNEL_ID,PROMO_ID',   
|

|   'orc.bloom.filter.fpp'='0.05',                                              
|

|   'orc.compress'='SNAPPY',                                                    
|

|   'orc.create.index'='true',                                                  
|

|   'orc.row.index.stride'='10000',                                             
|

|   'orc.stripe.size'='268435456',                                              
|

|   'transient_lastDdlTime'='1451814921')                                       
|

+-------------------------------------------------------------------------------+--+

 

And loaded data from smallsales to sales table

 

Stats updated in both

 

Now when I do the following

 

0: jdbc:hive2://rhes564:10010/default> select * from smallsales where prod_id = 
10;

+---------------------+---------------------+---------------------+------------------------+----------------------+---------------------------+-------------------------+--+

| smallsales.prod_id  | smallsales.cust_id  | smallsales.time_id  | 
smallsales.channel_id  | smallsales.promo_id  | smallsales.quantity_sold  | 
smallsales.amount_sold  |

+---------------------+---------------------+---------------------+------------------------+----------------------+---------------------------+-------------------------+--+

+---------------------+---------------------+---------------------+------------------------+----------------------+---------------------------+-------------------------+--+

No rows selected (2.231 seconds)

 

Ok if I do the same query from partitioned bucketed table in takes 

 

0: jdbc:hive2://rhes564:10010/default> select * from sales where prod_id = 10;

+----------------+----------------+----------------+-------------------+-----------------+----------------------+--------------------+-------------+--------------+--+

| sales.prod_id  | sales.cust_id  | sales.time_id  | sales.channel_id  | 
sales.promo_id  | sales.quantity_sold  | sales.amount_sold  | sales.year  | 
sales.month  |

+----------------+----------------+----------------+-------------------+-----------------+----------------------+--------------------+-------------+--------------+--+

+----------------+----------------+----------------+-------------------+-----------------+----------------------+--------------------+-------------+--------------+--+

No rows selected (26.96 seconds)

 

 

Note that the second query is order of magnitude slower. 

 

My view is that the query in partitioned table has got to go through every 
partitioned file to check the existence of the value, whereas in a 
non-partitioned table the operation is much faster.  Adding more partition and 
buckets also adds more load on NameNode as well.

 

Are there other reasons?

 

Thanks

 

 

 

Dr Mich Talebzadeh

 

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Oracle and Sybase, Concepts and Contrasts, ISBN: 978-0-9563693-1-4, volume one 
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