Two optimizations:
1. Insert string bytes directly to remove decoding&encoding process.
2. Use native reader to read the hudi base file if it has no log file. Use `explain` to show how many splits are read natively.
When converting query results into MySQL format, it involves transforming columnar data storage into row-based storage. This process raises the question of choosing between sequential reading and sequential writing. In reality, sequential writing is the better choice for performance optimization.
Test with 9M rows contains more than 20 columns, this patch can reduce the conversion time from 20s to 11s.
Fix bug of left and full outer join with other conjuncts. When equal matched row count of a probe row exceed batch_size, some times the _join_node->_is_any_probe_match_row_output flag is not set correcty, which result in outputing extra rows for the probe row.
in order to solve agg of sum/count is not compatibility during the upgrade process.
in PR [refactor](agg_state) refactor agg_state type to support fixed length object type #20370 have changed the serialize type and serialize column of sum/count
before is ColumnVector, now sum/count change to use ColumnFixedLengthObject
so during the upgrade process, will be not compatible if exist Old BE and Newer BE
* [Bug](topn opt) Fix Two-Phase read when some rowset swept
If this is a Two-Phase read query, and we need to delay the release of Rowset by row->update_delayed_expired_timestamp() to expand the lifespan of rowsets. This is necessary to avoid data loss during the second phase reading, where some stale rowsets may be swept and result in missing data.
When FE is old version, be is new version, issue a schema change(add column) and
then query, old version of FE query without schema version could result in reading
stale schema from schema cache
1. Add hdfs file handle cache for hdfs file reader
Copied from Impala, `https://github.com/apache/impala/blob/master/be/src/util/lru-multi-cache.h`. (Thanks for the Impala team)
This is a lru cache that can store multi entries with same key.
The key is build with {file name + modification time}
The value is the hdfsFile pointer that point to a certain hdfs file.
This cache is to avoid reopen same hdfs file mutli time, which can save
query time.
Add a BE config `max_hdfs_file_handle_cache_num` to limit the max number
of file handle cache, default is 20000.
2. Add file meta cache
The file meta cache is a lru cache. the key is {file name + modification time},
the value is the parsed file meta info of the certain file, which can save
the time of re-parsing file meta everytime.
Currently, it is only used for caching parquet file footer.
The test show that is cache is hit, the `FileOpenTime` and `ParseFooterTime` is reduce to almost 0
in query profile, which can save time when there are lots of files to read.
The java-udf module has become increasingly large and difficult to manage, making it inconvenient to package and use as needed. It needs to be split into multiple sub-modules, such as : java-commom、java-udf、jdbc-scanner、hudi-scanner、 paimon-scanner.
Co-authored-by: lexluo <lexluo@tencent.com>
After supporting insert-only transactional hive full acid tables #19518, #19419, this PR support transactional hive full acid tables.
Support hive3 transactional hive full acid tables.
Hive2 transactional hive full acid tables need to run major compactions.
Currently, there are many profiles using add child profile to orgnanize profile into blocks. But it is wrong. Child profile will have a total time counter. Actually, what we should use is just a label.
- MemoryUsage:
- HashTable: 23.98 KB
- SerializeKeyArena: 446.75 KB
Add a new macro ADD_LABEL_COUNTER to add just a label in the profile.
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Co-authored-by: yiguolei <yiguolei@gmail.com>
PR(https://github.com/apache/doris/pull/19909) has implemented the framework of hudi reader for MOR table. This PR completes all functions of reading MOR table and enables end-to-end queries.
Key Implementations:
1. Use hudi meta information to generate the table schema, not from hive client.
2. Use hive client to list hudi partitions, so it strongly depends the sync-tools(https://hudi.apache.org/docs/syncing_metastore/) which syncs the partitions of hudi into hive metastore. However, we may get the hudi partitions directly from .hoodie directory.
3. Remove `HudiHMSExternalCatalog`, because other catalogs like glue is compatible with hive catalog.
4. Read the COW table originally from c++.
5. Hudi RecordReader will use ProcessBuilder to start a hotspot debugger process, which may be stuck when attaching the origin JNI process, soI use a tricky method to kill this useless process.
