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The README.md file is displayed on the github home page https://github.com/apache/impala Change this so that the opening line mentions “data stored in open data and table formats” instead of “data stored in Apache Hadoop clusters“. Also add Iceberg as the first mentioned place where data can be stored. Change-Id: I35e91611374f20ec6a540d4c3bf5ae375ac38bce Reviewed-on: http://gerrit.cloudera.org:8080/20783 Reviewed-by: Quanlong Huang <huangquanlong@gmail.com> Tested-by: Michael Smith <michael.smith@cloudera.com>
70 lines
3.1 KiB
Markdown
70 lines
3.1 KiB
Markdown
# Welcome to Impala
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Lightning-fast, distributed [SQL](https://en.wikipedia.org/wiki/SQL) queries for petabytes
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of data stored in open data and table formats.
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Impala is a modern, massively-distributed, massively-parallel, C++ query engine that lets
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you analyze, transform and combine data from a variety of data sources:
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* Best of breed performance and scalability.
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* Support for data stored in [Apache Iceberg](https://iceberg.apache.org/), [HDFS](https://hadoop.apache.org/),
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[Apache HBase](https://hbase.apache.org/), [Apache Kudu](https://kudu.apache.org/),
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[Amazon S3](https://aws.amazon.com/s3/),
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[Azure Data Lake Storage](https://azure.microsoft.com/en-us/services/storage/data-lake-storage/),
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[Apache Hadoop Ozone](https://hadoop.apache.org/ozone/) and more!
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* Wide analytic SQL support, including window functions and subqueries.
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* On-the-fly code generation using [LLVM](http://llvm.org/) to generate lightning-fast
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code tailored specifically to each individual query.
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* Support for the most commonly-used Hadoop file formats, including
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[Apache Parquet](https://parquet.apache.org/) and [Apache ORC](https://orc.apache.org).
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* Support for industry-standard security protocols, including Kerberos, LDAP and TLS.
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* Apache-licensed, 100% open source.
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## More about Impala
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The fastest way to try out Impala is a [quickstart Docker container](
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https://github.com/apache/impala/blob/master/docker/README.md#docker-quickstart-with-docker-compose).
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You can try out running queries and processing data sets in Impala on a single machine
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without installing dependencies. It can automatically load test data sets into Apache Kudu
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and Apache Parquet formats and you can start playing around with Apache Impala SQL
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within minutes.
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To learn more about Impala as a user or administrator, or to try Impala, please
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visit the [Impala homepage](https://impala.apache.org). Detailed documentation for
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administrators and users is available at
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[Apache Impala documentation](https://impala.apache.org/impala-docs.html).
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If you are interested in contributing to Impala as a developer, or learning more about
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Impala's internals and architecture, visit the
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[Impala wiki](https://cwiki.apache.org/confluence/display/IMPALA/Impala+Home).
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## Supported Platforms
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Impala only supports Linux at the moment.
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Impala supports x86_64 and has experimental support for arm64 (as of Impala 4.0).
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[Impala Requirements](https://impala.apache.org/docs/build/html/topics/impala_prereqs.html)
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contains more detailed information on the minimum CPU requirements.
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## Supported OS Distributions
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Impala runs on Linux systems only. The supported distros are
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* Ubuntu 16.04/18.04
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* CentOS/RHEL 7/8
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Other systems, e.g. SLES12, may also be supported but are not tested by the community.
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## Export Control Notice
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This distribution uses cryptographic software and may be subject to export controls.
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Please refer to EXPORT\_CONTROL.md for more information.
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## Build Instructions
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See [Impala's developer documentation](https://cwiki.apache.org/confluence/display/IMPALA/Impala+Home)
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to get started.
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[Detailed build notes](README-build.md) has some detailed information on the project
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layout and build.
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