Cloudera Impala Cumulative Sum, Average and Example

You can make use of the Cloudera impala Analytic functions to calculate the cumulative sum or running sum. Sum and Average analytical functions are used along with window options to calculate the Cloudera Impala Cumulative Sum or running sum. Cloudera Impala Cumulative Sum, Average Syntax: Below are the Syntax for Cloudera Impala Cumulative SUM, AVG analytic functions. You can defined ORDER BY clause with column inside OVER clause. SUM([DISTINCT| ALL] expression)[OVER (analytic_clause)] AVG([DISTINCT| ALL] expression)[OVER (analytic_clause)] Cloudera Impala Cumulative Sum, Average Examples Impala Cumulative Sum and Average. Query: select name, amount,…

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Generate Netezza Table DDL using nz_ddl_table

If you are working as a Netezza admin then you may be asked to get DDL of all tables available in the particular database. You can still do that in hard way such as using Aginity workbench, WinSQL, or Squirrel workbench. This this article, we are going to discuss the easy way to generate Netezza Table DDL using nz_ddl_table. Generate Netezza Table DDL using nz_ddl_table nz_ddl_table is a Netezza provided utility and is used to generate the Netezza table DDL from particular database. Utility will generate the DDL for all table…

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Netezza CREATE GROUP Command

A group with one or more members is a user group. User groups are used to simplify access management. In this article, we will discuss about the Netezza Create Group command. Netezza CREATE GROUP Command Each and every member of the user group inherits its privileges and other settings. For e.g. you may want to create the user groups called Developers, Admins etc. Each user group will be provided with set of privileges that each members inherits upon adding to it. Netezza CREATE GROUP command Syntax CREATE GROUP name [WITH…

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Netezza COPY Command Syntax and Examples

The Netezza COPY command moves data between IBM Netezza tables and standard file system files, sometimes to standard output. Netezza COPY Command Use the COPY command with a file name to read directly from or write to a file. The nzload command is much faster and stable compared to COPY command. Netezza always recommends using nzload instead of COPY command. Netezza does not recommend using the COPY command. For load/unload operations use the nzload command or CREATE EXTERNAL TABLE commands. These commands are faster and more stable than the COPY…

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Netezza Transaction Management – BEGIN, COMMIT, ROLLBACK

A transaction is a series of one or more operations on database-related objects and/or data. The transaction management is process of ensuring the transaction is successfully completed and commited in the Netezza database. In this article, we will discuss about the Netezza transaction management using BEGIN, COMMIT and ROLLBACK.  Read: Netezza CREATE TABLE command and Examples  Database ACID Properties and Explanation Clustered base table in Netezza  IBM Netezza Alter Table Command and Examples  Netezza Create User Command and Examples You can execute the DDL statements in transactions. Statements executed outside of…

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Netezza Alter User Command and Examples

Once you created a user, you can change the parameters of the user at any time with Netezza ALTER USER command. You can read my other post Netezza CREATE USER command and examples. Netezza Alter User Command Syntax In the Netezza, username, database name and group name are unique. You cannot have same user as the group name. Read: IBM Netezza Alter Table Command and Examples How to Resolve Netezza too many Concurrent Sessions issue? Netezza Create User Command and Examples Syntax for altering a user: ALTER USER username [WITH [PASSWORD…

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Netezza Create User Command and Examples

Use the Netezza CREATE USER command to define a new database user account. You can specify the parameters like password, expire date, default priority etc to the user while creating an account. Netezza Create User Command Syntax In the Netezza, username, database name and group name are unique. You cannot have same user as the group name. Syntax for creating a user: CREATE USER username [WITH [PASSWORD {'string' | NULL }] [SYSID uid] [ROWSETLIMIT [integer ] [IN GROUP groupname [, ...] ] [VALID UNTIL 'date' ] [SESSIONTIMEOUT [integer ] [QUERYTIMEOUT…

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Netezza Regular Expression Functions and Examples

The Netezza regular expression functions identify precise patterns of characters and are useful for extracting string from the data and validation of the existing data, for example, validate date, range checks, checks for characters, and extract specific characters from the data. All these Netezza regular expressions are added in the Netezza SQL extension toolkit. Read: Download and install Netezza SQL toolkit extension IBM Netezza Update Join Syntax and Examples Netezza Extract Functions and Examples Netezza Extract Numbers using Regular Expressions In this article, we will check out some of the…

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Netezza Extract Numbers using Regular Expressions

IBM has introduced some of new functions in its latest version of Netezza. The new features include bunch of useful regular expression. All these new functions are available as a part of Netezza SQL toolkit extension. In this article, we will discuss about Netezza extract numbers using regular expressions. Read: Download and install Netezza SQL toolkit extension Netezza Pivot Rows to Column With Example Netezza Extract Functions and Examples IBM Netezza Regular Expression Functions and Examples Netezza Extract Numbers using Regular Expressions Below are the some of the examples for Netezza…

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Netezza Implicit Skew with an Example

Netezza Implicit Skew is the Netezza skew that occurs within the database when processing large data sets. The implicit Netezza skew are very difficult to identify. You can read more on Netezza Skew and How to avoid it. Netezza Implicit Skew Netezza implicit skew is occurs when data get redistributed or broadcasted on some other column to perform join operations. Data will be redistributed or broadcasted to perform co-located joins. The column on which data get redistributed or joined could be skewed that is, most of the redistributed data get inserted to…

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