Netezza

Netezza RECORD Type Variable, Usage and Examples

Just like other procedural language, Netezza supports RECORD type variables. Netezza RECORD type variable are similar to row types, but they have no predefined structure associated with it. You can use the record type only inside Netezza stored procedures (SP). They are used in selections and FOR loops to hold one database row from a SELECT operation. Read about Netezza Stored Procedure here: Netezza Stored Procedure and Examples IBM Netezza Control structures and usage Netezza Stored Procedure ARRAY Variables and Examples Netezza RECORD type Variable Declaration Below is the syntax…

Continue ReadingNetezza RECORD Type Variable, Usage and Examples
Comments Off on Netezza RECORD Type Variable, Usage and Examples
November 5, 2017
BigData

Hadoop – Export Hive Data with Quoted Values into Flat File and Example

In general, quoted values are values which are enclosed in single or double quotation marks. Usually, quoted values files are system generated where each and every fields in flat files is either enclosed in SINGLE or DOUBLE quotation mark. In this article, we will check how to export Hadoop Hive data with quoted values into flat file such as CSV file format. Quoted Value File Overview In the quoted values files, values are enclosed in quotation mark in case there is a embedded delimiter. For example, comma separated values file…

Continue ReadingHadoop – Export Hive Data with Quoted Values into Flat File and Example
Comments Off on Hadoop – Export Hive Data with Quoted Values into Flat File and Example
November 5, 2017
Netezza

Export Netezza Data with Quoted Values into Flat File and Example

In general, quoted values are values which are enclosed in single or double quotes. Usually, quoted values files are system generated where each and every fields in flat files is either enclosed in SINGLE or DOUBLE quotation mark. In this article, we will check how to export Netezza data with quoted values into flat file such as CSV format. Quoted Value File Overview As mentioned in the previous section, quoted values files contains the values that are enclosed either in SINGLE or DOUBLE quotation mark. Generally, values are enclosed in…

Continue ReadingExport Netezza Data with Quoted Values into Flat File and Example
Comments Off on Export Netezza Data with Quoted Values into Flat File and Example
November 4, 2017
Netezza

Extract Netezza Table into Fixed-width file format and Example

Fixed width text files are special cases of text files. In a fixed width file, the format is specified by column widths, pad character and left or right alignment. In this format column width are in terms of units of characters. Fixed-width files has field (column) withe same predefined width in each file row, similar to a spreadsheet table. In this article, we will check how to extract Netezza table into fixed-width file format with a working examples. The examples of fixed width files would be telecom CDR (call detail…

Continue ReadingExtract Netezza Table into Fixed-width file format and Example
Comments Off on Extract Netezza Table into Fixed-width file format and Example
November 3, 2017
Data Warehouse

Data Warehouse fact-less fact Tables and Examples

A Data Warehouse fact-less fact table is a fact that does not have any measures stored in it. This table will only contain keys from different dimension tables. The fact-less fact is often used to resolve a many-to-many cardinality issue. Types of Fact-less fact tables in Data Warehouse? There are two types of fact-less fact tables Event capturing fact-less fact This type of fact table establishes the relationship among the various dimension members from various dimension tables without any measured value. For examples, Student attendance (student-teacher relation table) capturing table…

Continue ReadingData Warehouse fact-less fact Tables and Examples
2 Comments
November 2, 2017
BigData

Hadoop Security – Hadoop HDFS File Permissions

Hadoop HDFS file permissions are almost similar to the POSIX file system. In a Linux system, we usually create OS level users and make them members of an existing operating system group. But in Hadoop, we create directory and associate it with an owner and a group. Hadoop HDFS File and Directory Permissions The following sections show Hadoop HDFS file and directory permissions: Just like Linux operating system, Hadoop uses notation (r,w) to denote read and write permissions. There is an execute (x) permission for files but you cannot execute…

Continue ReadingHadoop Security – Hadoop HDFS File Permissions
Comments Off on Hadoop Security – Hadoop HDFS File Permissions
November 2, 2017
Data Warehouse

Data Warehouse Two-tier Architecture in Details

Usually, data warehouse adapts either two-tier or three-tier architecture. We have discussed three-tire architecture in my other post 'Data Warehouse Three-tier Architecture'. In this article, we will discuss on the data warehouse two-tier architecture. Data Warehouse Two-tier Architecture  The data warehouse two-tier architecture is a client - server application. There is a direct communication between client and data source server, we call it as data layer or database layer. Usually, there is no intermediate application between client and database layer. Below diagram depicts data warehouse two-tier architecture: As shown in…

Continue ReadingData Warehouse Two-tier Architecture in Details
Comments Off on Data Warehouse Two-tier Architecture in Details
October 31, 2017
Data Warehouse

Data Warehouse Surrogate Key Design – Advantages and Disadvantages

If you are working on Data warehouse project, than you might have heard lot about surrogate keys. Surrogate keys are widely accepted data warehouse design standard. In this article, we will check data warehouse surrogate key design, advantages and disadvantages. What are surrogate keys in Data warehouse? If you are a data warehouse developer, that you might be thinking what is surrogate key? How and where it is being used? You will get answers to all your questions here. Data warehouse surrogate keys are sequentially generated meaningless numbers associated with…

Continue ReadingData Warehouse Surrogate Key Design – Advantages and Disadvantages
2 Comments
October 31, 2017
BigData

Migrating Netezza Data to Hadoop Ecosystem and Sample Approach

In my other post ‘Migrating Netezza to Impala SQL Best Practices’, we have discussed various best practices to migrate the Netezza SQL scripts to Impala SQL. In this article, we will discuss steps on Migrating Netezza Data to Hadoop Ecosystem. Migrating Netezza Data to Hadoop Ecosystem – Offload Netezza data to Hadoop HDFS Now a days Hadoop ecosystem is gaining popularity and organization with huge data wants to migrate to Hadoop ecosystem for their faster analytics that includes real-time or near real-time. Steps to Migrating Netezza Data to Hadoop Ecosystem…

Continue ReadingMigrating Netezza Data to Hadoop Ecosystem and Sample Approach
2 Comments
October 30, 2017
Data Warehouse

Data Warehouse Project Life Cycle and Design

Building data warehouse is not different than executing other development project such as front-end application. You need to be technical and business person who understand technical details along with organizations business to successfully design and implement data warehouse project. In this article, we will check what the data warehouse project life cycle is and different steps in designing data warehouse project! Steps of Data Warehouse Project Life Cycle Design Following are steps generally followed in any data warehouse projects you can consider these steps as data warehouse lifecycle: Requirements gathering…

Continue ReadingData Warehouse Project Life Cycle and Design
Comments Off on Data Warehouse Project Life Cycle and Design
October 30, 2017