DataGenX - Atul's Blog: Administration

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Saturday, 23 June 2018

yet another In Memory DataBase - MemSQL

by Unknown / in Administration, Database, In-Memory, Installation, Linux, memory, MemSQL /

Writing this post after so many days, yet another IN-MEMORY database is in market which tag line promised with"The DataBase for Real-Time Applications".

As per MemSQL site - MemSQL is a scalable SQL database that ingests data continuously to perform operational analytics for the front lines of your business. Ingest millions of events per day with ACID transactions while simultaneously analyzing billions of rows of data in relational SQL, JSON, or Geospatial formats.

In my current assignment, I've been asked to look into the capabilities of this db, so starting with very first step "Installation" -

Installation in linux is quite simple, if you are OK with linux commands, You can follow the installation from HERE

1. Download the software (with sudo or root user) -

sudo su - root
wget http://download.memsql.com/memsql-ops-6.0.11/memsql-ops-6.0.11.tar.gz

2. Extract the tar ball

tar zxvf memsql-ops-6.0.11.tar.gz

This command will extract lots n lots of files :-)

3. Run the installer script

cd memsql-ops-6.0.11

sudo ./install.sh --simple-cluster

By default, MemSQL supports the machine with 4 cpu core and 8 GB of RAM (which is little unfair;-)) so remove this constraints by below argument -

cd memsql-ops-6.0.11

sudo ./install.sh --simple-cluster --ignore-min-requirements

After being successful installation of MemSQL, it will start setting up MemSQL WebUI.

You can access the MemSQL WebUI on the sever's 9000 port by default.

https://<SERVER_IP>:9000

4. To connect to MemSQL command line, execute -

memsql

In next post, I will explain how this db is different than other in-memory db. Till then, Keep Learning , Keep Loving.

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Mongo DB - Installation and Configuration

by Unknown / in Administration, commands, Concept, Configuration, Database, DBMS, install, Linux, MongoDB, NoSQL /

MongoDB is an open-source document database, and the leading NoSQL database. Written in C++.

MongoDB features:
    Document-Oriented Storage
    Full Index Support
    Replication & High Availability
    Auto-Sharding
    Querying
    Fast In-Place Updates
    Map/Reduce
    GridFS

Reduce cost, accelerate time to market, and mitigate risk with proactive support and enterprise-grade capabilities.

Today, We will see how to install and run the MongoDB.

MongoDB Installation on Linux

1. DOWNLOAD the stable version of MongoDB. It will a tar file
2. Extract the tar file to some directory.

$ tar -xvf mongodb.tar -C /learn/mongodb

3. change the permisson of folder to user who run the db here- In my case User - hduser and Group - hadoop
$ chown -R hduser:hadoop /learn/mongodb

4. Add the env var in .bashrc
export MONGO_HOME=/learn/mongodb
export PATH=$PATH:$MONGO_HOME/bin

5. Create the default DB directory for Mongo
$ mkdir -R /data/db
$ chown -R hduser:hadoop /data/db
This is by default, you can specify ur db path when starting the mongo db

$ mongod --dbpath /app/mongodata
this command will start the mongodb. in other terminal you can start work on db. "--dbpath /app/mongodata" is totally optional

If you just use just $ mongod , it will start n use the default db which we have defined in step 5.

Please don't close the current terminal, It can be kill the mongodb process.

6. Start working on MongoDB
$ mongo

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How to get DataStage Project Settings

by Unknown / in Administration, Batch, Datastage, Environment, Password, Project, Properties, Script, User, Variable, Windows /

DSListProjectSettings.bat is used to report all available settings of existing projects.

USAGE: DSListProjectSettings <SERVER> <USER> <PASSWORD> <PROJECT>

The DSListProjectSettings batch file reports all available project settings and environment variable names and values to standard output. The first section shows available DataStage project properties and their settings. The second section shows environment variable names and values. When run successfully, each section will report a status code of zero.

PDF Split & Merge with Perl

by Unknown / in Administration, perl, Script, Shell Script /

Sharing two utility scripts (Perl), which can be used for extracting only few pages from a PDF file and also for combining different pdf files into a single pdf files. There might be lot of situation where in, we might require only few pages from a big PDF files. So instead of storing / carrying such a big PDF files, we could extract the page or pages which we require from the original big PDF files. Also we could combine different pdf files into a single pdf file using the second script. As an example, if we have extracted pages 10-15 and pages 100-120 from a big pdf file using the pdf_extract.pl and
we can combine these two pdf files (i.e. pdf which contains pages 10-15 and pdf which contains
pages 100-120) into a single pdf file using pdf_merge.pl

NOTE : These two perl scripts uses a perl module called PDF::API2. If this is not present on your system as part of the perl installation, you can download these modules from www.cpan.org and install. Please see the installation section for more details.

These two scripts can be used on windows, unix or linux. Currently tested on Windows with active perl 5.8.8, but it should work on unix and linux as well. For the pdf_extract.pl script to work on unix and linux, please change the variable called "path_separator" to "/" instead of "\\". This variable can be seen at the starting of the script. pdf_merge.pl can be used both on windows and unix/linux without any modification

Usage:

1) pdf_extract.pl

perl pdf_extract.pl -i <input pdf file> -p <page or page range which needs to be extracted>

where
-i : Please give the full path to the input PDF file
-p : Page Number or Page range which needs to be extracted from the input PDF

example : To extract pages 3 to 5, execute

perl pdf_extract.pl -i /tmp/abc.pdf -p 3-5

example : To extract only page 3, execute

perl pdf_extract.pl -i /tmp/abc.pdf -p 3

Executing with -h option will display the usage onto the screen

Example : perl ./pdf_extract.pl -h

2) pdf_merge.pl

perl pdf_merge.pl <output pdf file with full path> <input pdf file 1> <input pdf file 2> etc

Execute the script with all the pdf file which needs to be merged.
Script will merge in the same order which is given in the input

i.e. If you execute like pdf_merge.pl /tmp/out.pdf /tmp/abc.pdf /tmp/xyz.pdf

then pages from xyz.pdf will be after pages from abc.pdf

Executing with -h option will display the usage onto the screen

Example : ./pdf_merge.pl -h

CodeBase:

README File:
pdf_extract.pl
pdf_merge.pl

Import the jobs from DS windows client #iLoveScripting

by Unknown / in Administration, Batch, Client, Datastage, dsjob, export, iLoveScripting, Import, Job, Jobs, Machine, Script, Windows /

As we have discussed a script which can export the datastage jobs from your client system (http://bit.ly/2frNPKj) likewise we can write another one to import the jobs. Let's see how -

DsImportJobsClient.bat :

This Script read all the *.dsx job name from the specified Directory and Sub-Directory and import to the Specified project. It can also build (Only BUILD) the existing package created on Information Server Manager and send it to the specified location on client machine.

To use the build feature you need to make sure the package has been created with all the needed jobs, saved and closed. Only update to the selected job will be taken care automatically. To add/delete a job, you need to do manually.

Modify the Import.properties and ImportJobList.txt file and Go the .bat dir and then execute the importAndBuild.bat.

Import.properties :

ImportJobList.txt :

DsImportJobsClient.bat :

Script to Auto Compress the System Log Files

by Unknown / in Administration, github, Linux, Maintenance, Monitor, Shell, Shell Script, System /

This Script is originally written by "Andy Welter" to compress the linux system log files. I have modified it to work better. You can find it below (modified version) -

Script Usage:
logroll [-compress|-nocompress]

$ logroll -compress
# compress the log files and move to archive directory

$ logroll -nocompress
# Move the file to archive directory with compressing it

=================================================================== ===================================================================

#3 How to Copy DataSet from One Server to Another Server

by Unknown / in Administration, Copy, data, dataset, Datastage, File, Move, Server, tips, tricks, Troubleshoot /

This post is third and last of How to Copy DataSet from One Server to Another Server Series

We have generated a populated a dataset and identified the files which we need to move to another server serverB from serverA

Continue.......

4. Reading the dataset on another server

This is the most crucial step, Now all 4 files are moved on serverB or the common location which can be accessible from serverB.

For my case, common dir is my home - /home/users/atul

A. Change the default.apt file
We need to change the fastname in default.apt (config file) which we copied from the serverA, [ NOT the default.apt for serverB]

Open the file in any text editor or vi and change as below screen shot -

Temporarily create the "resource disk" and "resource scratchdisk" location if not existing as defined in above config file.

B. Copy the dataset data files

Move the dataset data file from common directory to "resource disk" as defined in config file.

cp ~/dummy.ds.* /opt/IBM/InformationServer/Server/DataSets/

Now, all files locations are like -

Config file and Dataset descriptor file - my home dir or common dir
Dataset data files - /opt/IBM/InformationServer/Server/DataSets/

Design a job which will read thess dataset files and populate data into sequential file or any other output.

Job Paramaters -
APT_CONFIG_FILE = /home/users/atul/default.apt

DataSet Properties
DataSet File - /home/users/atul/dummy.ds

That is all, you can read the copied dataset on serverB, you can populate this data to some other output such as seq file, table so that you can avoid the use of copied default.apt config file which is not for serverB.

Try it out, let me know if you have any question.

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#2 How to Copy DataSet from One Server to Another Server

by Unknown / in Administration, Copy, data, dataset, Datastage, File, Move, Server, tips, tricks, Troubleshoot /

This post is second part of How to Copy DataSet from One Server to Another Server

Continue.......

After generating the dummy dataset, next step is to identify the files which we need to copy.

2. Files which we need to move

a. APT_CONFIG_FILE - configuration file which used in dataset
b. DataSet Descriptor file - *.ds file, in our case it is dummy.ds
c. DataSet Data files - Actual data files which stored in RESOURCE DISK location

So let's get all the path which we need to access -

APT_CONFIG_FILE = /opt/IBM/InformationServer/Server/Configulations/default.apt
RESOURCE DISK = /opt/IBM/InformationServer/Server/DataSets
DATASET LOC = /home/users/atul/dummy.ds

Use commands or any FTP tool to copy these files in a shared location which can be accessible from another server (serverB)

For my case, I have stored all of them into my linux home direcory which is common in both server.

So I have executed these commands to copy all the required files into my home directory.

cp /opt/IBM/InformationServer/Server/Configulations/default.apt ~
cp /opt/IBM/InformationServer/Server/DataSets/dummy.ds.* ~
cp /home/users/atul/dummy.ds ~

Now, my home directory is having these files -

You can copy these 4 files on serverB where you want to move your dataset. I am not doing the same as my home directory is common for both server.

3. Why we need these files only

Config file was used by datastage to create dataset ( descriptot file, data files, data file location)
So, we needed - config file, dataset descriptor file and dataset data files.

#1 How to Copy DataSet from One Server to Another Server

by Unknown / in Administration, Atul, Copy, data, dataset, Datastage, File, Move, Server, tips, tricks, Troubleshoot /

Hi Guys...
I've been asked so many times that how can we move/copy one dataset from one server to another So here is the way which I follow.

At very first step, Analyze if you can avoid this by using some other way like creating sequential file and ftp Or load the data into temporary table which can be accessible on another server, if using datastage packs then via mqs, xml or json formats etc. Why I am suggesting these solutions coz these are easy to design and guaranteed the data quality at other end.

If above solutions are not possible, please follow the below steps -

Points I am going to cover here -
1. Generating a dummy dataset
2. Files which we need to move
3. Why we need these files only
4. Reading the dataset on another server

http://www.datagenx.net/2016/06/datastage-quiz-1.html

1. Generating a dummy dataset

I have created a dummy job which is generating a dataset with default APT_Config_file which has 2 nodes.

http://www.datagenx.net/2015/12/how-to-use-universe-shell-uvsh-in.html

Here, I am generating 10 dummy rows with the help of Row Generator stage and storing them into a datasset.

a. Config File - I am using the default config file (replaced the server name in "fastname" with serverA)

APT_CONFIG_FILE = /opt/IBM/InformationServer/Server/Configulations/default.apt

http://www.datagenx.net/2016/06/5-tips-for-better-datastage-design-14.html

check out the "resource disk" location in config file, we need it for further processing

RESOURCE DISK = /opt/IBM/InformationServer/Server/DataSets

b. dataset location - I have created this dataset in my home dir named dummy.ds

DATASET LOC = /home/atul/dummy.ds

Keep looking for next post........

Tuning SQL Statement #4

by Unknown / in Administration, DB2, DBMS, Oracle, SQL, tips, tricks, Tuning /

Using Functions in QueriesWhen using functions in SQL statements it is best to keep the functions away from any columns involving index matching unless function-based indexes are available and can be created.

Do’s
SELECT account_name, trans_date, amount
FROM transaction
WHERE account_name LIKE 'CAPITAL%';

Don’ts
SELECT account_name, trans_date, amount
FROM transaction
WHERE SUBSTR(account_name,1,7) = 'CAPITAL';

Sequences
A sequence is often used to create unique integer identifiers as primary keys for tables. A sequence is a distinct database object and is accessed as sequence.NEXTVAL and sequence.CURRVAL.
Use sequences for unique integer identifiers; they are centralized, more controllable, more easily maintained, and perform better than other methods of counting.

Do’s
INSERT INTO supplier (supplier_id, name, ticker)
      VALUES (supplier_seq.NEXTVAL,'A new supplier', 'TICK');

Don’ts
INSERT INTO supplier (supplier_id, name, ticker)
      VALUES ((SELECT MAX(supplier_id)+1
      FROM supplier), 'A new supplier', 'TICK');



Equi, Anti, and Range
Using an equals sign (equi) is the fastest comparison condition if a unique index exists. Any type of anti comparison such as != or NOT is looking for what is not in a table and thus must read the entire table; sometimes full index scans can be used.

Do’s
SELECT account_name, trans_date, amount
FROM transaction
WHERE amount > 0;   SELECT account_name, trans_date, amount
FROM transaction
WHERE amount != 0;

Don’ts
SELECT account_name, trans_date, amount
FROM transaction
WHERE amount > 0;   SELECT account_name, trans_date, amount
FROM transaction
WHERE amount NOT = 0;

LIKE Pattern MatchingIn general, since LIKE will match patterns which are in no way related to indexes, LIKE will usually read an entire table.

Tuning SQL Statement #3

by Unknown / in Administration, DB2, DBMS, Oracle, SQL, tips, tricks, Tuning /

Tuning SQL Statement #1.......
Tuning SQL Statement #2.......

Consider whether a UNION ALL will suffice in place of a UNION.
The UNION statement performs the equivalent of a SELECT DISTINCT on the final result set. In other words, the UNION clause forces all rows returned by each portion of the UNION to be sorted and merged and duplicate to be filtered before the first row is returned. A UNION ALL simply returns all rows including duplicates and does not have to perform any sort, merge or filter. If your tables are mutually exclusive (include no duplicate records), or you don't care if duplicates are returned, the UNION ALL is much more efficient as it does not perform the SELECT DISTINCT function, which saves a lot of unnecessary resources from being used.

Do’s
SELECT acct_num, balance_amt
FROM debit_transactions
WHERE tran_date = '1-JAN-06'
UNION ALL
SELECT acct_num, balance_amt
FROM credit_transactions
WHERE tran_date = '1-JAN-06' ;

Don’ts
SELECT acct_num, balance_amt
FROM debit_transactions
WHERE tran_date = '1-JAN-06'
UNION
SELECT acct_num, balance_amt
FROM credit_transactions
WHERE tran_date = '1-JAN-06' ;

http://www.datagenx.net/2016/04/tuning-select-statement-2.html

The DECODE Function
Using the DECODE function as a replacement for multiple query set operators is good for performance but should only be used in extreme cases such as the UNION clause joined SQL statements as shown.

Do’s
SELECT stock_id||' '||
      DECODE(SIGN(qtyonhand)
            ,-1,'Out of Stock',0,'Out of Stock'
            ,1,DECODE(SIGN(qtyonhand-min)
                   ,-1,'Under Stocked',0,'Stocked'
                   ,1,DECODE(sign(qtyonhand-max)
                        ,-1,'Stocked',0,'Stocked'
                          ,1,'Over Stocked'
                   )
            )
      ) FROM stock;


Don’ts
SELECT stock_id||' Out of Stock' FROM stock WHERE
   qtyonhand <=0
UNION
SELECT stock_id||' Under Stocked' FROM stock
      WHERE qtyonhand BETWEEN 1 AND min-1
UNION
SELECT stock_id||' Stocked' FROM stock
WHERE qtyonhand BETWEEN min AND max
UNION
SELECT stock_id||' Over Stocked' FROM stock
      WHERE qtyonhand > max;



Datatype Conversions
Try to avoid using any type of data conversion function in any part of an SQL statement which could potentially match an index, especially if you are trying to assist performance by matching appropriate indexes.

Do’s
SELECT ...
FROM customer
WHERE cust_id = TO_NUMBER('11');   SELECT ...
FROM customer
WHERE cust_id = '11';

Don’ts
SELECT ...
FROM customer
WHERE cust_type = 1;   SELECT ...
FROM emp
WHERE TO_NUMBER (cust_type) = 1;

Tuning SQL Statement #2

by Unknown / in Administration, DB2, DBMS, Oracle, SQL, tips, tricks, Tuning /

Tuning SQL Statement #1.......
Tuning SQL Statement #3.......

• The UNION statement performs the equivalent of a SELECT DISTINCT on the final result set. In other words, the UNION clause forces all rows returned by each portion of the UNION to be sorted and merged and duplicate to be filtered before the first row is returned. A UNION ALL simply returns all rows including duplicates and does not have to perform any sort, merge or filter. If your tables are mutually exclusive (include no duplicate records), or you don't care if duplicates are returned, the UNION ALL is much more efficient as it does not perform the SELECT DISTINCT function, which saves a lot of unnecessary resources from being used.

Do's-
SELECT acct_num, balance_amt FROM debit_transactions WHERE tran_date = '1-JAN-06'
UNION ALL
SELECT acct_num, balance_amt FROM credit_transactions WHERE tran_date = '1-JAN-06' ;

Don'ts-
SELECT acct_num, balance_amt FROM debit_transactions WHERE tran_date = '1-JAN-06'
UNION
SELECT acct_num, balance_amt FROM credit_transactions WHERE tran_date = '1-JAN-06' ;

•   Try to avoid using any type of data conversion function in any part of an SQL statement which could potentially match an index, especially if you are trying to assist performance by matching appropriate indexes

Do's-
SELECT ... FROM customer
WHERE cust_id = TO_NUMBER('11');

SELECT ... FROM customer
WHERE cust_type = 1;

Don'ts-
SELECT ... FROM customer
WHERE cust_id = '11';

SELECT ... FROM emp
WHERE TO_NUMBER (cust_type) = 1;

•   When using functions in SQL statements it is best to keep the functions away from any columns involving index matching unless function-based indexes are available and can be created.

Do's-
SELECT account_name, trans_date, amount FROM transaction
WHERE account_name LIKE 'CAPITAL%';

Don'ts-
SELECT account_name, trans_date, amount FROM transaction
WHERE SUBSTR(account_name,1,7) = 'CAPITAL';

•   If your SELECT statement contains a HAVING clause, write your query so that the WHERE clause does most of the work (removing undesired rows) instead of the HAVING clause do the work of removing undesired rows. Using the WHERE clause appropriately can eliminate unnecessary rows before they get to the GROUP BY and HAVING clause, saving some unnecessary work, and boosting performance

Do's-
SELECT country, AVG (population) FROM survey
WHERE country != 'INDIA'
AND country != 'CHINA';
GROUP BY country;

Don'ts-
SELECT country, AVG (population) FROM survey
GROUP BY country
HAVING country != ‘INDIA'
AND country != 'CHINA’;

•   The ORDER BY clause is always executed after the WHERE clause. Try not to override the WHERE clause with the ORDER BY clause because the Optimizer may choose a less efficient method of execution based on the ORDER BY clause. Try to put your where columns in order by clause if possible.

Do's-
SELECT * FROM ordersline
WHERE order_id < 10
ORDER BY order_id, seq#;

Don'ts-
SELECT * FROM ordersline
WHERE order_id < 10
ORDER BY seq#;

Tuning SQL Statement #1

by Unknown / in Administration, DB2, DBMS, Oracle, SQL, tips, tricks, Tuning /

•   Try to use explicit columns and try to read columns in index orders if possible, even to the point of reading indexes and not tables.
•   Use a standard approach to table aliases. If two identical SQL statements vary because an identical table has two different aliases, then the SQL is different and will not be shared.
•   Use table aliases and prefix all column names by their aliases when more than one table is involved in a query. This reduces parse time AND prevents future syntax errors if someone adds a column to one of the tables with the same name as a column in another table.
•   Use bind variables. The values of bind variables do not need to be the same for two statements to be considered identical. Bind variables are not substituted until a statement has been successfully parsed.

i.e -
Do's    - Select FirstNme, MidName, LastName from atul.employee;
Don'ts - Select * from atul.employee;

•   Try to match comparison condition column sequences with existing index column sequences, although it is not strictly necessary.
•   Always try to use unique, single-column indexes wherever possible. A single-column unique index is much more likely to produce exact hits. An exact hit is the fastest access method.
•   Try to avoid WHERE clauses that are NEGATIVE. Negative key words are in the WHERE clause, such as "IS NULL", "<>", "!=", "!>", "!<", "NOT", "NOT EXISTS", "NOT IN", "NOT LIKE"

i.e -
Do's    - Select FirstNme from atul.employee where DeptCd Like 'IN%';
Don'ts - Select FirstNme from atul.employee where SubSTR(DeptCd, 1,2) = 'IN';

Do's    - Select Material from atul.store where quantity > 0;
Don'ts - Select Material from atul.store where quantity <> 0;

Do's    - Select Material from atul.store where quantity > 3;
Don'ts - Select Material from atul.store where quantity + 3 > 6;

Tuming SELECT Statement Continues...............

ETL Development Standards

by Unknown / in Administration, Code, develop, Development, ETL, Guide, Guidelines, Naming, Standards /

These development standards provide consistency in the artifacts the ETL developers create. This consistency improves testing, operational support, maintenance, and performance.

Code Development Guidelines

1 Commenting in Code and Objects

As a primary guideline where it is possible and does not interfere with the operation of the applications, all code must contain a developer comment/note.
• All ETL jobs must have a proper annotation (short description of the functionality of the job).
• The target output files (.csv files) should not contain any leading or trailing spaces.
• While deciding record level delimiter, “Delimiter Collision” issue needs to be considered. No such delimiter should be used as a field defaults that is present as a part of data.

2 ETL Naming Standards

The standardized naming conventions ease the burden on developers switching from one project to another. Knowing the names and where things are located are very useful to understand before the occurrence of the design and development phases.

The following table identifies DataStage elements and their standard naming convention.

2.1 Job and Properties Naming Conventions

GUI Component	Entity	Convention
Designer	Parallel Job	<<Application>>_<<job_Name>>_JOB
Designer	Sequence	<<Application>>_<<job_Name>>_SEQ
Designer	Server Job	<<Application>>_<<job_Name>>_SVR
Designer	Parameter	<<Application>>_<<job_Name>>_PARM

2.2 Job Processing Stage Naming Conventions

GUI Component	Entity	Convention
Designer	Aggregator	AGG_<<PrimaryFunction>>
Designer	Copy	CP_<<PrimaryFunction>>
Designer	Filter	FLT_<<PrimaryFunction>>
Designer	Funnel	FNL_<<PrimaryFunction>>
Designer	Join (Inner)	JN_<<PrimaryFunction>>
Designer	FTP Enterprise	FTP_<<PrimaryFunction>>
Designer	Lookup	LKP_<< Value Name or table Name>>
Designer	Merge	MRG_<<PrimaryFunction>>
Designer	Modify	MOD_<<PrimaryFunction>>
Designer	Sort	SRT_<<PrimaryFunction>>

2.3 Links Naming Conventions

GUI Component	Entity	Convention
Designer	Reference (Lookup)	Lnk_Ref_<<Number or Additional descriptor, if needed to form a unique object name>>
Designer	Reject (Lookup, File, DB)	Lnk_Rej_<<Number or Additional descriptor, if needed to form a unique object name>>
Designer	Input	Lnk_In_<<Number or Additional descriptor, if needed to form a unique object name>>
Designer	Output	Lnk_Out_<<Number or Additional descriptor, if needed to form a unique object name>>
Designer	Delete	Lnk_Del_<<Number or Additional descriptor, if needed to form a unique object name>>
Designer	Insert	Lnk_Ins_<<Number or Additional descriptor, if needed to form a unique object name>>
Designer	Update	Lnk_Upd_<<Number or Additional descriptor, if needed to form a unique object name>>

2.4 Data Store Naming Conventions:

In the case of a data store, the class word refers to the type of data store (e.g. Dataset, Sequential File, Table, View, and so forth).

GUI Component	Entity	Convention
Designer	Database	DB_<<DatabasName>>
Designer	Table	TBL_<<TableName>>
Designer	View	VIEW_<<ViewName>>
Designer	Dimension	DM_<<TableName>>
Designer	Fact	TRAN_<<TableName>>
Designer	Source	SRC_<<Table or Object Name>>
Designer	Target	TRGT_<<Table or objectName>>

2.5 File Stage Naming Conventions:

GUI Component	Entity	Convention
Designer	Sequential File	SEQ_
Designer	Complex Flat File	CFF_
Designer	Parallel dataset	DS_

Saturday, 23 June 2018

Sunday, 14 January 2018

MongoDB Installation on Linux

Sunday, 5 March 2017

Tuesday, 21 February 2017

Wednesday, 7 December 2016

DsImportJobsClient.bat :

Wednesday, 12 October 2016

Wednesday, 3 August 2016

4. Reading the dataset on another server

Monday, 1 August 2016

2. Files which we need to move

3. Why we need these files only

Saturday, 30 July 2016

1. Generating a dummy dataset

Tuesday, 7 June 2016

Monday, 23 May 2016

Wednesday, 27 April 2016

Tuesday, 26 April 2016

Tuesday, 1 March 2016

Code Development Guidelines

1 Commenting in Code and Objects

2 ETL Naming Standards

2.1 Job and Properties Naming Conventions

2.2 Job Processing Stage Naming Conventions

2.3 Links Naming Conventions

2.4 Data Store Naming Conventions:

2.5 File Stage Naming Conventions: