Re: Impact of partitioning on certain queries
https://snippetessay.wordpress.com/2015/07/25/hive-optimizations-with-indexes-bloom-filters-and-statistics/ Maybe a compact index makes more sense if you have high cardinality columns > On 08 Jan 2016, at 10:11, Mich Talebzadeh wrote: > > 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 > > LinkedIn > https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw > > Sybase ASE 15 Gold Medal Award 2008 > A Winning Strategy: Running the most Critical Financial Data on ASE 15 > http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf > Author of the books "A Practitioner’s Guide to Upgrading to Sybase ASE 15", > ISBN 978-0-9563693-0-7. > co-author "Sybase Transact SQL Guidelines Best Practices", ISBN > 978-0-9759693-0-4 > Publications due shortly: > Complex Event Processing in Heterogeneous Environments, ISBN: > 978-0-9563693-3-8 > Oracle and Sybase, Concepts and Contrasts, ISBN: 978-0-9563693-1-4, volume > one out shortly > > http://talebzadehmich.wordpress.com > > NOTE: The information in this email is proprietary and confidential. This > message is for the designated recipient only, if you are not the intended > recipient, you should destroy it immediately. Any information in this message > shall not be understood as given or endorsed by Peridale Technology Ltd, its > subsidiaries or their employees, unless expressly so stated. It is the > responsibility of the recipient to ensure that this email is virus free, > therefore neither Peridale Ltd, its subsidiaries nor their employees accept > any responsibility. > > 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 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 > > LinkedIn > https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw > > Sybase ASE 15 Gold Medal Award 2008 > A Winning Strategy: Running the most Critical Financial Data on ASE 15 > http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf > Author of the books "A Practitioner’s Guide to Upgrading to Sybase ASE 15", > ISBN 978-0-9563693-0-7. > co-author "Sybase Transact SQL Guidelines Best Practices", ISBN > 978-0-9759693-0-4 > Publications due shortly: > Complex Event Processing in Heterogeneous Environments, ISBN: > 978-0-9563693-3-8 > Oracle and Sybase, Concepts and Contrasts, ISBN: 978-0-9563693-1-4, volume >
RE: Impact of partitioning on certain queries
Thanks helpful
0: jdbc:hive2://rhes564:10010/default> explain dependency select * from sales
where year = 2001 and month = 12;
+---+--+
|
Explain
|
+---+--+
|
{"input_partitions":[{"partitionName":"oraclehadoop@sales@year=2001/month=12"}],"input_tables":[{"tablename":"oraclehadoop@sales","tabletype":"MANAGED_TABLE"}]}
|
In above sales is partitioned on year and month.
My interpretation is that only that partition is searched for?
Dr Mich Talebzadeh
LinkedIn
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Sybase ASE 15 Gold Medal Award 2008
A Winning Strategy: Running the most Critical Financial Data on ASE 15
<http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf>
http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf
Author of the books "A Practitioner’s Guide to Upgrading to Sybase ASE 15",
ISBN 978-0-9563693-0-7.
co-author "Sybase Transact SQL Guidelines Best Practices", ISBN
978-0-9759693-0-4
Publications due shortly:
Complex Event Processing in Heterogeneous Environments, ISBN: 978-0-9563693-3-8
Oracle and Sybase, Concepts and Contrasts, ISBN: 978-0-9563693-1-4, volume one
out shortly
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From: Jörn Franke [mailto:jornfra...@gmail.com]
Sent: 08 January 2016 09:54
To: user@hive.apache.org
Subject: Re: Impact of partitioning on certain queries
Try explain dependency
On 08 Jan 2016, at 10:47, Mich Talebzadeh mailto:m...@peridale.co.uk> > wrote:
Thanks Gopal.
Basically the following is true:
1.The storage layer is HDFS
2.The execution engine is MR, Tez, Spark etc
3.The access layer is Hive
When we say the access layer is Hive, is the assumption correct that we are
referring to optimiser (loosly related to the optimiser in RDBMS). For example
is Hive optimiser aware of the number of underlying partitions. The reason I am
asking this question is that with EXPLAIN I only see Table scan and it does
refer to any partition or partition elimination?
Cheers
NOTE: The information in this email is proprietary and confidential. This
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recipient, you should destroy it immediately. Any information in this message
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-Original Message-
From: Gopal Vijayaraghavan [mailto:go...@hortonworks.com] On Behalf Of Gopal
Vijayaraghavan
Sent: 08 January 2016 09:34
To: user@hive.apache.org <mailto:user@hive.apache.org>
Subject: Re: Impact of partitioning on certain queries
> Ok we hope that partitioning improves performance where the predicate
>is on partitioned columns
Nope.
Partitioning *only* improves performance if your queries run with
set hive.mapred.mode=strict;
That's the "use strict" easy way to make sure you're writing good queries.
Even then, schema design in hive is something you need to learn with the
assumption that neither the storage layer, nor the compute layer is part of
"hive".
It floats itself in an "access" layer above both. Not sure there's any legacy
tech to draw parallels with that.
If you haven't seen this before, here's an example of the problem
<http://www.slideshare.net/Hadoop_Summit/hive-at-yahoo-letters-from-the-tren>
http://www.slideshare.net/Hadoop_Summit/hive-at-yahoo-letters-from-the-tren
ches/24
Cheers,
Gopal
Re: Impact of partitioning on certain queries
Try explain dependency > On 08 Jan 2016, at 10:47, Mich Talebzadeh wrote: > > Thanks Gopal. > > Basically the following is true: > > 1.The storage layer is HDFS > 2.The execution engine is MR, Tez, Spark etc > 3.The access layer is Hive > > When we say the access layer is Hive, is the assumption correct that we are > referring to optimiser (loosly related to the optimiser in RDBMS). For > example is Hive optimiser aware of the number of underlying partitions. The > reason I am asking this question is that with EXPLAIN I only see Table scan > and it does refer to any partition or partition elimination? > > > Cheers > > > NOTE: The information in this email is proprietary and confidential. This > message is for the designated recipient only, if you are not the intended > recipient, you should destroy it immediately. Any information in this message > shall not be understood as given or endorsed by Peridale Technology Ltd, its > subsidiaries or their employees, unless expressly so stated. It is the > responsibility of the recipient to ensure that this email is virus free, > therefore neither Peridale Ltd, its subsidiaries nor their employees accept > any responsibility. > > > -Original Message- > From: Gopal Vijayaraghavan [mailto:go...@hortonworks.com] On Behalf Of Gopal > Vijayaraghavan > Sent: 08 January 2016 09:34 > To: user@hive.apache.org > Subject: Re: Impact of partitioning on certain queries > > > > Ok we hope that partitioning improves performance where the predicate > >is on partitioned columns > > Nope. > > Partitioning *only* improves performance if your queries run with > > set hive.mapred.mode=strict; > > That's the "use strict" easy way to make sure you're writing good queries. > > Even then, schema design in hive is something you need to learn with the > assumption that neither the storage layer, nor the compute layer is part of > "hive". > > It floats itself in an "access" layer above both. Not sure there's any legacy > tech to draw parallels with that. > > If you haven't seen this before, here's an example of the problem > > http://www.slideshare.net/Hadoop_Summit/hive-at-yahoo-letters-from-the-tren > ches/24 > > > Cheers, > Gopal
RE: Impact of partitioning on certain queries
Thanks Gopal. Basically the following is true: 1.The storage layer is HDFS 2.The execution engine is MR, Tez, Spark etc 3.The access layer is Hive When we say the access layer is Hive, is the assumption correct that we are referring to optimiser (loosly related to the optimiser in RDBMS). For example is Hive optimiser aware of the number of underlying partitions. The reason I am asking this question is that with EXPLAIN I only see Table scan and it does refer to any partition or partition elimination? Cheers NOTE: The information in this email is proprietary and confidential. This message is for the designated recipient only, if you are not the intended recipient, you should destroy it immediately. Any information in this message shall not be understood as given or endorsed by Peridale Technology Ltd, its subsidiaries or their employees, unless expressly so stated. It is the responsibility of the recipient to ensure that this email is virus free, therefore neither Peridale Ltd, its subsidiaries nor their employees accept any responsibility. -Original Message- From: Gopal Vijayaraghavan [mailto:go...@hortonworks.com] On Behalf Of Gopal Vijayaraghavan Sent: 08 January 2016 09:34 To: user@hive.apache.org Subject: Re: Impact of partitioning on certain queries > Ok we hope that partitioning improves performance where the predicate >is on partitioned columns Nope. Partitioning *only* improves performance if your queries run with set hive.mapred.mode=strict; That's the "use strict" easy way to make sure you're writing good queries. Even then, schema design in hive is something you need to learn with the assumption that neither the storage layer, nor the compute layer is part of "hive". It floats itself in an "access" layer above both. Not sure there's any legacy tech to draw parallels with that. If you haven't seen this before, here's an example of the problem <http://www.slideshare.net/Hadoop_Summit/hive-at-yahoo-letters-from-the-tren > http://www.slideshare.net/Hadoop_Summit/hive-at-yahoo-letters-from-the-tren ches/24 Cheers, Gopal
Re: Impact of partitioning on certain queries
> Ok we hope that partitioning improves performance where the predicate is >on partitioned columns Nope. Partitioning *only* improves performance if your queries run with set hive.mapred.mode=strict; That's the "use strict" easy way to make sure you're writing good queries. Even then, schema design in hive is something you need to learn with the assumption that neither the storage layer, nor the compute layer is part of "hive". It floats itself in an "access" layer above both. Not sure there's any legacy tech to draw parallels with that. If you haven't seen this before, here's an example of the problem http://www.slideshare.net/Hadoop_Summit/hive-at-yahoo-letters-from-the-tren ches/24 Cheers, Gopal
RE: Impact of partitioning on certain queries
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 LinkedIn <https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw Sybase ASE 15 Gold Medal Award 2008 A Winning Strategy: Running the most Critical Financial Data on ASE 15 <http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf> http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf Author of the books "A Practitioner’s Guide to Upgrading to Sybase ASE 15", ISBN 978-0-9563693-0-7. co-author "Sybase Transact SQL Guidelines Best Practices", ISBN 978-0-9759693-0-4 Publications due shortly: Complex Event Processing in Heterogeneous Environments, ISBN: 978-0-9563693-3-8 Oracle and Sybase, Concepts and Contrasts, ISBN: 978-0-9563693-1-4, volume one out shortly <http://talebzadehmich.wordpress.com/> http://talebzadehmich.wordpress.com NOTE: The information in this email is proprietary and confidential. This message is for the designated recipient only, if you are not the intended recipient, you should destroy it immediately. Any information in this message shall not be understood as given or endorsed by Peridale Technology Ltd, its subsidiaries or their employees, unless expressly so stated. It is the responsibility of the recipient to ensure that this email is virus free, therefore neither Peridale Ltd, its subsidiaries nor their employees accept any responsibility. 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 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 LinkedIn <https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw Sybase ASE 15 Gold Medal Award 2008 A Winning Strategy: Running the most Critical Financial Data on ASE 15 <http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf> http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf Author of the books "A Practitioner’s Guide to Upgrading to Sybase ASE 15", ISBN 978-0-9563693-0-7. co-author "Sybase Transact SQL Guidelines Best Practices", ISBN 978-0-9759693-0-4 Publications due shortly: Complex Event Processing in Heterogeneous Environments, ISBN: 978-0-9563693-3-8 Oracle and Sybase, Concepts and Contrasts, ISBN: 978-0-9563693-1-4, volume one out shortly <http://talebzadehmich.wordpress.com/> http://talebzadehmich.wordpress.com NOTE: The information in this email is proprietary and confidential. This message is for the designated recipient only, if you are not the inten
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 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 > > LinkedIn > https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw > > Sybase ASE 15 Gold Medal Award 2008 > A Winning Strategy: Running the most Critical Financial Data on ASE 15 > http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf > Author of the books "A Practitioner’s Guide to Upgrading to Sybase ASE 15", > ISBN 978-0-9563693-0-7. > co-author "Sybase Transact SQL Guidelines Best Practices", ISBN > 978-0-9759693-0-4 > Publications due shortly: > Complex Event Processing in Heterogeneous Environments, ISBN: > 978-0-9563693-3-8 > Oracle and Sybase, Concepts and Contrasts, ISBN: 978-0-9563693-1-4, volume > one out shortly > > http://talebzadehmich.wordpress.com > > NOTE: The information in this email is proprietary and confidential. This > message is for the designated recipient only, if you are not the intended > recipient, you should destroy it immediately. Any information in this message > shall not be understood as given or endorsed by Peridale Technology Ltd, its > subsidiaries or their employees, unless expressly so stated. It is the > responsibility of the recipient to ensure that this email is virus free, > therefore neither Peridale Ltd, its subsidiaries nor their employees accept > any responsibility. > > From: Jörn Franke [mailto:jornfra...@gmail.com] > Sent: 08 January 2016 06:20 > To: 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 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 A
RE: Impact of partitioning on certain queries
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 LinkedIn <https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw Sybase ASE 15 Gold Medal Award 2008 A Winning Strategy: Running the most Critical Financial Data on ASE 15 <http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf> http://login.sybase.com/files/Product_Overviews/ASE-Winning-Strategy-091908.pdf Author of the books "A Practitioner’s Guide to Upgrading to Sybase ASE 15", ISBN 978-0-9563693-0-7. co-author "Sybase Transact SQL Guidelines Best Practices", ISBN 978-0-9759693-0-4 Publications due shortly: Complex Event Processing in Heterogeneous Environments, ISBN: 978-0-9563693-3-8 Oracle and Sybase, Concepts and Contrasts, ISBN: 978-0-9563693-1-4, volume one out shortly <http://talebzadehmich.wordpress.com/> http://talebzadehmich.wordpress.com NOTE: The information in this email is proprietary and confidential. This message is for the designated recipient only, if you are not the intended recipient, you should destroy it immediately. Any information in this message shall not be understood as given or endorsed by Peridale Technology Ltd, its subsidiaries or their employees, unless expressly so stated. It is the responsibility of the recipient to ensure that this email is virus free, therefore neither Peridale Ltd, its subsidiaries nor their employees accept any responsibility. From: Jörn Franke [mailto:jornfra...@gmail.com] Sent: 08 January 2016 06:20 To: 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 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 (
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 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'='500', | > | '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 (
Impact of partitioning on certain queries
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'='500', | | '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'='1', | | '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 | +
