[CARBONDATA-3945] Fix NullPointerException of data loading

Why is this PR needed?
1. getLastModifiedTime of LoadMetadataDetails fails due to "updateDeltaEndTimestamp is empty string".
2. In the getCommittedIndexFile founction, NPE happens because of "segmentfile is null" under the Unusual cases.
3. Cleaning temp files fails because of "partitionInfo is null" under the unusual cases.
4. When calculating sizeInBytes of CarbonRelation, under the unusual cases, it need to collect the directory size. but the directory path only works for non-partition tables, for partition tables, filenotfoundexcepiton was throwed.

What changes were proposed in this PR?
1. when updateDeltaEndTimestamp is empty string, skip the code "convertTimeStampToLong(updateDeltaEndTimestamp)";
2. when segmentfile is null, avoid trigger "segmentfile.getSegmentMetaDataInfo()"
3. init partitionInfo with a empty list instead of "null"
4. Add a judgment condition, to avoid scan directory path for partitiontable when the directroy path only works for non-partitiontable.

Does this PR introduce any user interface change?
No

Is any new testcase added?
Yes

This closes #3881
5 files changed
tree: c88ec865fafd39c57b8c3b9c8fb320939c0852c0
  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

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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).