o8 impala

1. Impala Architecture Impala is a real-time interactive SQL Big Data Query Tool developed by cloudera under the inspiration of Google's dremel. Impala no longer uses slow hive + mapreduce batch processing, instead, it uses a distributed query engine similar to that in commercial parallel relational databases (composed of three parts: Query planner, query coordin

Cloudera impala is an engine that runs distributed queries on HDFS and hbase.This source is a snapshot of our internal development version. We regularly update the version.This readme document describes how to use this source to build cloudera Impala. For more information, see: Https://ccp.cloudera.com/display/IMPALA10BETADOC/Cloudera+Impala+1.0+Beta+Documentat

The SQL parsing and execution plan generation of Impala is implemented by impala-frontend (Java), and the listening port is 21000. The user submits a request through the Beeswax interface BeeswaxService. query (). The processing logic at the impalad end is determined by voidImpalaServer: query (QueryHandlequery_handle, constQueryquery ). The SQL parsing and execution plan generation of

Hive and Impala as a data query tool, how do they query the data? What tools do we use to interact with Impala and hive? We first make clear Hive and the Impala the interface for the corresponding query is provided separately:(1) command Line Shell :1. Impala : Impala Shel

This article is based on Hadoop yarn and Impala under the CDH releaseIn earlier versions of Impala, in order to use Impala, we typically started the Impala-server, Impala-state-store, and Impala-catalog services in a client/server

latency of MapReduce.To achieve Impala and HBase integration, we can obtain the following benefits: We can use familiar SQL statements. Like traditional relational databases, it is easy to provide SQL Design for complex queries and statistical analysis. Impala query statistics and analysis is much faster than native MapReduce and Hive. To integrate Impala wi

This article mainly introduces how impala-backend executes a SQLQuery. In Impala, The SQLQuery entry function is voidImpalaServer: query (QueryHandlequery_handle, constQueryquery) to generate a QueryExecState with the lifecycle of the SQL statement execution, which indicates the SQL statement being executed. Call E This article describes how impala-backend execut

2. Impala source code analysis Reference: http://www.sizeofvoid.net/wp-content/uploads/ImpalaIntroduction2.pdf This chapter begins the source code analysis stage. The reference link is a very good introduction to Impala implementation and running process. Thank you for the author.2.1 Impala internal architecture The internal architecture of

Hive and Impala are data query tools built on top of Hadoop, so how do they load and store data in real-world applications? Hive and Impala store and load tables, like all relational databases, have their own data management structure, from its server to database to tables and views. In other databases, tables are stored in their own specific file format, such as Oracle has its own storage format, and for h

A recent project, on the Big Data Transformation Project, the bottom choice Impala or sparksql it?Finally, choose Impala. This opens up my Impala learning journey. I am responsible for most of the Imapa interface development work.I am unable to control the whole to understand and learn. All are also tested and studied in the