* Update Hive sync timestamp when change detected
Only update the last commit timestamp on the Hive table when the table schema
has changed or a partition is created/updated.
When using AWS Glue Data Catalog as the metastore for Hive this will ensure
that table versions are substantive (including schema and/or partition
changes). Prior to this change when a Hive sync is performed without schema
or partition changes the table in the Glue Data Catalog would have a new
version published with the only change being the timestamp property.
https://issues.apache.org/jira/browse/HUDI-1932
* add conditional sync flag
* fix testSyncWithoutDiffs
* fix HiveSyncConfig
Co-authored-by: Raymond Xu <2701446+xushiyan@users.noreply.github.com>
* [HUDI-2285] Adding Synchronous updates to metadata before completion of commits in data timelime.
- This patch adds synchronous updates to metadata table. In other words, every write is first committed to metadata table followed by data table. While reading metadata table, we ignore any delta commits that are present only in metadata table and not in data table timeline.
- Compaction of metadata table is fenced by the condition that we trigger compaction only when there are no inflight requests in datatable. This ensures that all base files in metadata table is always in sync with data table(w/o any holes) and only there could be some extra invalid commits among delta log files in metadata table.
- Due to this, archival of data table also fences itself up until compacted instant in metadata table.
All writes to metadata table happens within the datatable lock. So, metadata table works in one writer mode only. This might be tough to loosen since all writers write to same FILES partition and so, will result in a conflict anyways.
- As part of this, have added acquiring locks in data table for those operations which were not before while committing (rollback, clean, compaction, cluster). To note, we were not doing any conflict resolution. All we are doing here is to commit by taking a lock. So that all writes to metadata table is always a single writer.
- Also added building block to add buckets for partitions, which will be leveraged by other indexes like record level index, etc. For now, FILES partition has only one bucket. In general, any number of buckets per partition is allowed and each partition has a fixed fileId prefix with incremental suffix for each bucket within each partition.
Have fixed [HUDI-2476]. This fix is about retrying a failed compaction if it succeeded in metadata for first time, but failed w/ data table.
- Enabling metadata table by default.
- Adding more tests for metadata table
Co-authored-by: Prashant Wason <pwason@uber.com>
* [HUDI-1848] Adding support for HMS for running DDL queries in hive-sync-tool
* [HUDI-1848] Fixing test cases
* [HUDI-1848] CR changes
* [HUDI-1848] Fix checkstyle violations
* [HUDI-1848] Fixed a bug when metastore api fails for complex schemas with multiple levels.
* [HUDI-1848] Adding the complex schema and resolving merge conflicts
* [HUDI-1848] Adding some more javadocs
* [HUDI-1848] Added javadocs for DDLExecutor impls
* [HUDI-1848] Fixed style issue
[global-hive-sync-tool] Add a global hive sync tool to sync hudi table across clusters. Add a way to rollback the replicated time stamp if we fail to sync or if we partly sync
Co-authored-by: Jagmeet Bali <jsbali@uber.com>
Main functions:
Support create table for hoodie.
Support CTAS.
Support Insert for hoodie. Including dynamic partition and static partition insert.
Support MergeInto for hoodie.
Support DELETE
Support UPDATE
Both support spark2 & spark3 based on DataSourceV1.
Main changes:
Add sql parser for spark2.
Add HoodieAnalysis for sql resolve and logical plan rewrite.
Add commands implementation for CREATE TABLE、INSERT、MERGE INTO & CTAS.
In order to push down the update&insert logical to the HoodieRecordPayload for MergeInto, I make same change to the
HoodieWriteHandler and other related classes.
1、Add the inputSchema for parser the incoming record. This is because the inputSchema for MergeInto is different from writeSchema as there are some transforms in the update& insert expression.
2、Add WRITE_SCHEMA to HoodieWriteConfig to pass the write schema for merge into.
3、Pass properties to HoodieRecordPayload#getInsertValue to pass the insert expression and table schema.
Verify this pull request
Add TestCreateTable for test create hoodie tables and CTAS.
Add TestInsertTable for test insert hoodie tables.
Add TestMergeIntoTable for test merge hoodie tables.
Add TestUpdateTable for test update hoodie tables.
Add TestDeleteTable for test delete hoodie tables.
Add TestSqlStatement for test supported ddl/dml currently.
HiveTestUtil static setup mini servers caused connection refused issue in Azure CI environment, as TestHiveSyncTool and TestHiveMetastoreBasedLockProvider share the same test facilities. Moving TestHiveMetastoreBasedLockProvider (the easier one) to functional test with a separate and improved mini server setup resolved the issue.
Also cleaned up dfs cluster from HiveTestUtil.
The next step is to move TestHiveSyncTool to functional as well.
* Reduces log level for too verbose messages from info to debug level.
* Sort config output.
* Code Review : Small restructuring + rebasing to master
- Fixing flaky multi delta streamer test
- Using isDebugEnabled() checks
- Some changes to shorten log message without moving to DEBUG
Co-authored-by: volodymyr.burenin <volodymyr.burenin@cloudkitchens.com>
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
