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Hadoop HDFS Architecture Introduction and Design

In this post you will learn about the Hadoop HDFS architecture introduction and its design. The Hadoop Distributed File System (HDFS) is a Java based distributed file system, designed to run on commodity hardwares. It has many similarities with existing available distributed file systems. Hadoop HDFS Architecture Introduction HDFS is highly fault-tolerant and is designed to be deployed on low-cost hardware. Hadoop HDFS provides high throughput access to application data and is suitable for applications that have large volume of data sets. HDFS has demonstrated production scalability of up to…

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December 3, 2016
BigData

Basic Hadoop HDFS Filesystem Operations With Examples

There are many interfaces to HDFS available, but the command line (CLI) is one of the simplest and, to many developers, the most familiar interface. You can perform most advanced and basic Hadoop HDFS filesystem operations using CLI. Basic Hadoop HDFS Filesystem Operations The when Hadoop HDFS filesystem is set, you can do all of the basic HDFS filesystem operations, such as reading files, creating directories, moving files, deleting data, and listing directories. You can also perform the advance Hadoop HDFS filesystem operations such as updates, administrator from command line.…

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October 31, 2016
BigData

Hadoop HDFS Schema Design for ETL Process

Now a day’s many organisations are using Hadoop for their ETL processing. In this post we will learn Hadoop HDFS Schema Design for ETL Process. In this section, you will learn about good schema design for data that you store in Hadoop HDFS directly. Hadoop HDFS Schema Design Overview Many organisation uses Hadoop for storing and processing unstructured, semi-structured or structured data. Hadoop is schema-on-read model that does not impose any requirements when loading data into Hadoop ecosystem. You can simply ingest data into Hadoop HDFS by using available ingestion…

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October 26, 2016
BigData

Hadoop Data Warehouse and Design Considerations

A data warehouse, also known as an enterprise data warehouse (EDW), is a large collective store of data that is used to make such data-driven decisions, thereby becoming one of the centrepiece of an organization’s data infrastructure. Hadoop Data Warehouse was challenge in initial days when Hadoop was evolving but now with lots of improvement, it is very easy to develop Hadoop data warehouse Architecture. This article will server as a guide to Hadoop data warehouse system design. Hadoop data warehouse integration is now a days become very much popular…

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October 26, 2016
BigData

Cloudera Impala Truncate Table Statement Examples

Cloudera Impala TRUNCATE TABLE statement removes all records from the table while keeping the table structure as it is. This statement is low overhead alternative for dropping and re-creating the tables. This statement is also low overhead compared to the INSERT OVERWRITE to replace the existing data from the HDFS directory before copying data. This is one of the features added in CDH 5.5 or higher. This statement helps when you are performing ELT/ELT operation cycles on Cloudera Impala where you have to empty the table after the data has…

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October 17, 2016
BigData

Cloudera Impala Generate Sequence Numbers without UDF

If you are migrating from traditional database to Cloudera Impala then you might have noticed there is not sequence number function. In the process of Cloudera Impala Generate Sequence Numbers without UDF, you can use analytical function that are available in Cloudera Impala. If you want generate sequential sequences that automatically keep in sync with your table sequence number, you can do so with the help of Cloudera impala supported ROW_NUMBER analytical function. Related reading: Impala Conditional Functions An Introduction to Cloudera Hadoop Impala Architecture Commonly used Impala shell Command…

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October 16, 2016
BigData

Run Impala SQL Script File Passing argument and Working Example

If you are porting Hive SQL scripts to Impala, you may come across passing variable to sql script as argument in Impala. You may get challenge to run Impala SQL script file passing argument. Prior to impala-shell version 2.5 there was no option to pass the value to script as arguments. Read: Impala Dynamic SQL Support and Alternative Approaches Run Hive Script File Passing Parameter and Working Example CDH 5.7/Impala shell version 2.5 and higher run Impala SQL Script File Passing argument. You can make use of the --var=variable_name option…

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October 14, 2016
BigData

Commonly used Impala shell Command Line Options

You can use the Impala shell interactive tool (impala-shell) to set up databases and tables, insert data, and issue queries. If you have worked on Netezza or Oracle, this tool is similar to nzsql and SQLPlus. For ad hoc queries and data exploration, you can submit SQL statements in an interactive session. You can write the queries in the script file and execute those using Impala shell Command Line Options. Read: Impala Conditional Functions An Introduction to Hadoop Impala Architecture Impala shell Command Line Options Command line Options Description -i…

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October 14, 2016
BigData

Impala Conditional Functions: IF, CASE, COALESCE, DECODE, NVL, ZEROIFNULL

Cloudera Impala supports the various Conditional functions. You can use these function for testing equality, comparison operators and check if value is null. Following are Impala Conditional Functions: Impala IF Conditional Function This is the one of best Impala Conditional Functions and is similar to the IF statements in other programming languages. Tests an expression and returns a corresponding result depending on whether the result is true, false or null. Read: An Introduction to Impala Architecture Syntax: if(boolean condition, type ifTrue, type ifFalseOrNull) For example; select if(1=1,'TRUE','FALSE') as IF_TEST; Impala CASE…

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October 13, 2016
BigData

An Introduction to Cloudera Hadoop Impala Architecture

Cloudera Hadoop impala architecture is very different compared to other database engine on HDFS like Hive. The Impala server is a distributed, massively parallel processing (MPP) database engine. The architecture is similar to the other distributed databases like Netezza, Greenplum etc. Hadoop impala consists of different daemon processes that run on specific hosts within your CDH cluster. Read: Sqoop Architecture Sqoop Import Sqoop Export Netezza and Hadoop Integration Hadoop HDFS Architecture Introduction and Design Cloudera Hadoop Impala Architecture Overview The Hadoop impala is consists of three components: The Impala Daemon,…

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October 13, 2016