Please also bear in mind that data in Hive supposed to be immutable (although
later version allow one to update data in Hive).
Data coming to Hive is supposed to be cleansed already sourced from other
transactional databases etc. So the concept of primary key (meaning enforcing
uniqueness for a row) does not make much sense in Hive. Indeed one often
demoralises data taking advantages of massive parallel processing in Hive.
External indexes in Hive can be created but are not useful as yet. In other
words Hive optimizer will not use them. For example these bitmap indexes on
the Fact table below are not used at all
0: jdbc:hive2://rhes564:10010/default> show index on sales;
+-----------------------+-----------------------+-----------------------+------------------------------------------+-----------------------+----------+--+
| idx_name | tab_name | col_names |
idx_tab_name | idx_type | comment |
+-----------------------+-----------------------+-----------------------+------------------------------------------+-----------------------+----------+--+
| sales_cust_bix | sales | cust_id |
oraclehadoop__sales_sales_cust_bix__ | bitmap | |
| sales_channel_bix | sales | channel_id |
oraclehadoop__sales_sales_channel_bix__ | bitmap | |
| sales_prod_bix | sales | prod_id |
oraclehadoop__sales_sales_prod_bix__ | bitmap | |
| sales_promo_bix | sales | promo_id |
oraclehadoop__sales_sales_promo_bix__ | bitmap | |
| sales_time_bix | sales | time_id |
oraclehadoop__sales_sales_time_bix__ | bitmap | |
+-----------------------+-----------------------+-----------------------+------------------------------------------+-----------------------+----------+--+
So this leaves us with storage indexes in Hive with ORC tables. If you are
importing CSV files, they can be imported as zipped (bzip2) files into
external staging tables and then inserted into Orc tables. That is the way I
would do that.
--1 Move .CSV data into HDFS:
--2 Create an external table.
--3 Create the ORC table.
--4 Insert the data from the external table to the Hive ORC table
--5 delete staging files
--1) hdfs dfs -copyFromLocal /var/tmp/t.bcp hdfs://rhes564:9000/data/stg/table
--1) hdfs dfs -copyFromLocal /var/tmp/t2.bcp hdfs://rhes564:9000/data/stg/table
--2) hdfs dfs -ls hdfs://rhes564:9000/data/stg/table
set hive.exec.reducers.max=256;
use test;
--2)
DROP TABLE IF EXISTS stg_t2;
CREATE EXTERNAL TABLE stg_t2 (
INVOICENUMBER string
,PAYMENTDATE string
,NET string
,VAT string
,TOTAL string
)
COMMENT 'from csv file from excel sheet PayInsPeridaleTechnology'
ROW FORMAT serde 'org.apache.hadoop.hive.serde2.OpenCSVSerde'
STORED AS TEXTFILE
LOCATION '/data/stg/table2'
TBLPROPERTIES ("skip.header.line.count"="1")
;
--3)
DROP TABLE IF EXISTS t2;
CREATE TABLE t2 (
INVOICENUMBER INT
,PAYMENTDATE timestamp
,NET DECIMAL(20,2)
,VAT DECIMAL(20,2)
,TOTAL DECIMAL(20,2)
)
COMMENT 'from csv file from excel sheet PayInsPeridaleTechnology'
STORED AS ORC
TBLPROPERTIES ( "orc.compress"="ZLIB" )
;
--4) Put data in target table. do the conversion and ignore empty rows
INSERT INTO TABLE t2
SELECT
INVOICENUMBER
, CAST(UNIX_TIMESTAMP(paymentdate,'DD/MM/YYYY')*1000 as timestamp)
--, CAST(REGEXP_REPLACE(SUBSTR(net,2,20),",","") AS DECIMAL(20,2))
, CAST(REGEXP_REPLACE(net,'[^\\d\\.]','') AS DECIMAL(20,2))
, CAST(REGEXP_REPLACE(vat,'[^\\d\\.]','') AS DECIMAL(20,2))
, CAST(REGEXP_REPLACE(total,'[^\\d\\.]','') AS DECIMAL(20,2))
FROM
stg_t2
WHERE CAST(REGEXP_REPLACE(net,'[^\\d\\.]','') AS DECIMAL(20,2)) > 0.0 --
Exclude empty rows
;
HTH,
Dr Mich Talebzadeh
LinkedIn
https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
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 <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
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From: Mich Talebzadeh [mailto:[email protected]]
Sent: 01 February 2016 15:58
To: [email protected]
Subject: RE: ORC format
In relational databases say Oracle or Sybase there is only one primary key for
a given table. So by definition you can have one primary key on any table
consists of one column or composite primary key (multiple columns).
Please check threads on “ORC files and statistics” in this forum.for detailed
explanation.
HTH
Dr Mich Talebzadeh
LinkedIn
https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
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 <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 Technology Ltd, its subsidiaries nor their employees
accept any responsibility.
From: Philip Lee [mailto:[email protected]]
Sent: 01 February 2016 15:49
To: [email protected] <mailto:[email protected]>
Subject: Re: ORC format
What do you mean by the silver bullet? so you mean it is not that stored as
primary key on each column. It is just stored as storage indexing, right?
"The statistics helps the optimiser. So whether one table or many, the
optimiser will take advantage of stats to push down the predicate for faster
decision." I understand this sentence when the operating tree is consisted of
filter function because when facing a filter function, it can skip the
unrelated rows. but do you think its aspect can be beneificial on joining two
tables as well?
On Mon, Feb 1, 2016 at 4:43 PM, Mich Talebzadeh <[email protected]
<mailto:[email protected]> > wrote:
Hi,
Orc table use what is known as storage index with stats (min, max. sum etc)
stored at the table, stripe and rowindex (rows of 10K batches) level. The
statistics helps the optimiser. So whether one table or many, the optimiser
will take advantage of stats to push down the predicate for faster decision.
Again ORC table is not a silver bullet. It can be valuable when conditions are
met.
HTH.
Dr Mich Talebzadeh
LinkedIn
https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
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 <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 Technology Ltd, its subsidiaries nor their employees
accept any responsibility.
From: Philip Lee [mailto:[email protected] <mailto:[email protected]> ]
Sent: 01 February 2016 15:21
To: [email protected] <mailto:[email protected]>
Subject: ORC format
Hello,
I experiment the performance of some systems between ORC and CSV file.
I read about ORC documentation on Hive website, but still curious of some
things.
I know ORC format is faster on filtering or reading because it has indexing.
Has it advantage of joining two tables of ORC dataset as well?
Could you explain about it in detail?
When experimenting, it seems like it has some advantages of joining in some
aspect, but not quite sure what characteristic of ORC make this happening
rather than CSV.
Best,
Phil
--
==========================================================
Hae Joon Lee
Now, in Germany,
M.S. Candidate, Interested in Distributed System, Iterative Processing
Dept. of Computer Science, Informatik in German, TUB
Technical University of Berlin
In Korea,
M.S. Candidate, Computer Architecture Laboratory
Dept. of Computer Science, KAIST
Rm# 4414 CS Dept. KAIST
373-1 Guseong-dong, Yuseong-gu, Daejon, South Korea (305-701)
Mobile) 49) 015-251-448-278 in Germany, no cellular in Korea
==========================================================
