Apache Impala is an open-source SQL query engine designed for efficient processing of large-scale data stored in a computer cluster running Apache Hadoop. It enables users to run real-time, interactive queries on massive datasets with remarkable speed. As a massively parallel processing tool, Apache Impala distributes workloads across multiple nodes, allowing for parallel execution of queries and accelerating data retrieval and analysis.
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- For Apache Hive users, Impala utilizes the same metadata and ODBC driver.
- It’s faster because Impala is an engine designed especially for the mission of interactive SQL over HDFS, and it has architecture concepts that helps it achieve that.
- Apache Impala is an open source massively parallel processing (MPP) SQL query engine for data stored in a computer cluster running Apache Hadoop.
- Impala provides fast, interactive SQL queries directly on your Apache Hadoop data stored in HDFS, HBase, or the Amazon Simple Storage Service (S3).
- It can automatically load test data sets into Apache Kudu and Apache Parquet formats and you can start playing around with Apache Impala SQL within minutes.
- Last commit:20 August 2024
- Whenever possible, Impala works with an existing Apache Hive infrastructure already used to execute long-running SQL batch queries.
- Security EnhancementFixed Issues in Apache Impala.
- New Features in Version 0.3 of the Impala Beta Release
- Apache Impala is a parallel processing SQL query engine that enables users to execute low latency SQL queries directly against large datasets stored in Apache...
- Impala can access data stored on HDFS in any of the Apache Hadoop file formats, including, Parquet, Text, Avro, RCFile and SequenceFile.
- Apache Impala raises the bar for the SQL query performance on Hadoop while retaining the familiar user experience.
