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Common Overview Single Node Setup Cluster Setup CLI Mini Cluster File System Shell Native Libraries Superusers Hadoop Commands Reference Service Level Authorization HTTP Authentication HDFS HDFS User Guide High Availability With QJM High Availability With NFS Federation HDFS Architecture Edits Viewer Image Viewer Permissions and HDFS Quotas and HDFS HFTP C API libhdfs WebHDFS REST API HttpFS Gatew
join_table: table_reference JOIN table_factor [join_condition] | table_reference {LEFT|RIGHT|FULL} [OUTER] JOIN table_reference join_condition | table_reference LEFT SEMI JOIN table_reference join_condition table_reference: table_factor | join_table table_factor: tbl_name [alias] | table_subquery alias | ( table_references ) join_condition: ON equality_expression ( AND equality_expression )* equal
Sqoop is a tool designed to transfer data between Hadoop and relational databases. You can use Sqoop to import data from a relational database management system (RDBMS) such as MySQL or Oracle into the Hadoop Distributed File System (HDFS), transform the data in Hadoop MapReduce, and then export the data back into an RDBMS. Sqoop automates most of this process, relying on the database to describe
flume-dev@cloudera.org version 0.9.1, September 10, 2010 Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. Being highly configurable and very extensible means that there are many options and thus many decisions that need to be made by an operator. This document is a "cookbook" with "recipes" for getting Flume up
flume-dev@cloudera.org version 0.9.0, June 29th 2010 Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. The system is centrally man
MRUnit is a unit test library designed to facilitate easy integration between your MapReduce development process and standard development and testing tools such as JUnit. MRUnit contains mock objects that behave like classes you interact with during MapReduce execution (e.g., InputSplit and OutputCollector) as well as test harness "drivers" that test your program's correctness while maintaining co
If you want to run Cloudera's Distribution for Hadoop (CDH) on Amazon's Elastic MapReduce (EMR), please visit our beta access request page. Running Hadoop on EC2 is easy. We've taken Cloudera's Distribution for Hadoop, and packaged it up in an easy-to-use AMI and associated launch scripts.Once you download and install the client scripts and enter your EC2 account info, bringing up a Hadoop cluster
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