THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
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Parquet is supported by Hive 0.10, 0.11, 0.12, and 0.13 |
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Summary
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Hive 0.10, 0.11, and 0.12
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Native Parquet support is pending for 0.13 via HIVE-5783.
Introduction
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Parquet (http://parquet.io/) is an ecosystem wide columnar format for Hadoop. At the time of this writing it supports:
Engines
- Apache Hive
- Apache Drill
- Cloudera Impala
- Apache Crunch
- Apache Pig
- Cascading
Data description
- Apache Avro
- Apache Thrift
- Google Protocol Buffers
The latest information on Parquet engine and data description support, please visit the Parquet-MR projects feature matrix.
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Format
The parquet project has an in-depth description of the format including motivations and diagrams.
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We created Parquet to make the advantages of compressed, efficient columnar data representation available to any project in the Hadoop ecosystem. Parquet is built from the ground up with complex nested data structures in mind, and uses the record shredding and assembly algorithm described in the Dremel paper. We believe this approach is superior to simple flattening of nested name spaces. Parquet is built to support very efficient compression and encoding schemes. Multiple projects have demonstrated the performance impact of applying the right compression and encoding scheme to the data. Parquet allows compression schemes to be specified on a per-column level, and is future-proofed to allow adding more encodings as they are invented and implemented. Parquet is built to be used by anyone. The Hadoop ecosystem is rich with data processing frameworks, and we are not interested in playing favorites. We believe that an efficient, well-implemented columnar storage substrate should be useful to all frameworks without the cost of extensive and difficult to set up dependencies. |
Hive QL Syntax
Hive 0.10 - 0.12
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- Binary, timestamp, date, char, varchar or decimal support are pending (HIVE-6384)
- Create Table AS SELECT (CTAS) and column rename support are pending (HIVE-6375)
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