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apache / carbondata / 57bcc9214e54219bcd76a3d19ba8446e4ed6dc8a
commit57bcc9214e54219bcd76a3d19ba8446e4ed6dc8a[log] [tgz]
authorakashrn5 <akashnilugal@gmail.com>Fri Jul 24 11:50:20 2020 +0530
committerkunal642 <kunalkapoor642@gmail.com>Mon Aug 24 16:52:29 2020 +0530
tree8b410ed89d721d61708c648daf32684dbd374c4f
parent34b63d67e54c3ea302e35d6e9f2513d7345b45dd [diff]
[CARBONDATA-3933]Fix DDL/DML failures after table is created
with column names having special characters like #,\,%

Why is this PR needed?
when operations like insert,describe, select is fired after
table is created with column names having special characters,
operations fails. This is because after table creation spark already
stred the column names with special characters correctly,
bt for further operations we try to update the metastore/refresh
with new schema parts which is unnecessary which causes this issue.

What changes were proposed in this PR?
We use unnecessary API to update the serde properties of table by
calling spark-sql, this was required when we used to support the
spark-2.1 and 2.2 version when spark was not supporting many alter
table operations. Now since we use other APIs to alter the table,
these API calls are not necessary. So once we remove we in turn
avoid updating the serde properties with the modified schema parts which solves this issue.

This closes #3862
13 files changed
tree: 8b410ed89d721d61708c648daf32684dbd374c4f
  1. .github/
  2. assembly/
  3. bin/
  4. build/
  5. common/
  6. conf/
  7. core/
  8. dev/
  9. docs/
  10. examples/
  11. format/
  12. geo/
  13. hadoop/
  14. index/
  15. integration/
  16. licenses-binary/
  17. mv/
  18. processing/
  19. python/
  20. sdk/
  21. streaming/
  22. tools/
  23. .gitignore
  24. LICENSE
  25. NOTICE
  26. pom.xml
  27. README.md
README.md

Apache CarbonData is an indexed columnar data store solution for fast analytics on big data platform, e.g.Apache Hadoop, Apache Spark, etc.

You can find the latest CarbonData document and learn more at: http://carbondata.apache.org

CarbonData cwiki

Visit count: HitCount

Status

Spark2.4: Build Status Coverage Status

Features

CarbonData file format is a columnar store in HDFS, it has many features that a modern columnar format has, such as splittable, compression schema ,complex data type etc, and CarbonData has following unique features:

  • Stores data along with index: it can significantly accelerate query performance and reduces the I/O scans and CPU resources, where there are filters in the query. CarbonData index consists of multiple level of indices, a processing framework can leverage this index to reduce the task it needs to schedule and process, and it can also do skip scan in more finer grain unit (called blocklet) in task side scanning instead of scanning the whole file.
  • Operable encoded data :Through supporting efficient compression and global encoding schemes, can query on compressed/encoded data, the data can be converted just before returning the results to the users, which is “late materialized”.
  • Supports for various use cases with one single Data format : like interactive OLAP-style query, Sequential Access (big scan), Random Access (narrow scan).

Building CarbonData

CarbonData is built using Apache Maven, to build CarbonData

Online Documentation

Experimental Features

Some features are marked as experimental because the syntax/implementation might change in the future.

  1. Hybrid format table using Add Segment.
  2. Accelerating performance using MV on parquet/orc.
  3. Merge API for Spark DataFrame.
  4. Hive write for non-transactional table.

Integration

Other Technical Material

Fork and Contribute

This is an active open source project for everyone, and we are always open to people who want to use this system or contribute to it. This guide document introduce how to contribute to CarbonData.

Contact us

To get involved in CarbonData:

About

Apache CarbonData is an open source project of The Apache Software Foundation (ASF).