Currently, compaction is executed separately for each backend, and the reconstruction of the index during compaction leads to high CPU usage. To address this, we are introducing single replica compaction, where a specific primary replica is selected to perform compaction, and the remaining replicas fetch the compaction results from the primary replica.
The Backend (BE) requests replica information for all peers corresponding to a tablet from the Frontend (FE). This information includes the host where the replica is located and the replica_id. By calculating hash(replica_id), the replica with the smallest hash value is responsible for executing compaction, while the remaining replicas are responsible for fetching the compaction results from this replica.
The compaction task producer thread, before submitting a compaction task, checks whether the local replica should fetch from its peer. If it should, the task is then submitted to the single replica compaction thread pool.
When performing single replica compaction, the process begins by requesting rowset versions from the target replica. These rowset_versions are then compared with the local rowset versions. The first version that can be fetched is selected.
This reverts commit 296b0c92f702675b92eee3c8af219f3862802fb2.
we can use drop table force stmt to fast drop tablets, no need to check tablet dropped state in every report
Co-authored-by: caiconghui1 <caiconghui1@jd.com>
See #17764 for details
I have tested:
- Unit test for local/s3/hdfs/broker file system: be/test/io/fs/file_system_test.cpp
- Outfile to local/s3/hdfs/broker.
- Load from local/s3/hdfs/broker.
- Query file on local/s3/hdfs/broker file system, with table value function and catalog.
- Backup/Restore with local/s3/hdfs/broker file system
Not test:
- cold & host data separation case.
Issue Number: close#16351
Dynamic schema table is a special type of table, it's schema change with loading procedure.Now we implemented this feature mainly for semi-structure data such as JSON, since JSON is schema self-described we could extract schema info from the original documents and inference the final type infomation.This speical table could reduce manual schema change operation and easily import semi-structure data and extends it's schema automatically.
1. support row format using codec of jsonb
2. short path optimize for point query
3. support prepared statement for point query
4. support mysql binary format
1. Change all required fields to optional
Although they all "required", but it not recommended to use `required`, because it is hard to modify in future.
2. Fix a missing field bug
* [Schema Change] support fast add/drop column (#49)
* [feature](schema-change) support fast schema change. coauthor: yixiutt
* [schema change] Using columns desc from fe to read data. coauthor: Lchangliang
* [feature](schema change) schema change optimize for add/drop columns.
1.add uniqueId field for class column.
2.schema change for add/drop columns directly update schema meta
Co-authored-by: yixiutt <yixiu@selectdb.com>
Co-authored-by: SWJTU-ZhangLei <1091517373@qq.com>
[Feature](schema change) fix write and add regression test (#69)
Co-authored-by: yixiutt <yixiu@selectdb.com>
[schema change] be ssupport that delete use newest schema
add delete regression test
fix regression case (#107)
tmp
[feature](schema change) light schema change exclude rollup and agg/uniq/dup key type.
[feature](schema change) fe olapTable maxUniqueId write in disk.
[feature](schema change) add rpc iface for sc add column.
[feature](schema change) add columnsDesc to TPushReq for ligtht sc.
resolve the deadlock when schema change (#124)
fix columns from fe don't has bitmap_index flag (#134)
add update/delete case
construct MATERIALIZED schema from origin schema when insert
fix not vectorized compaction coredump
use segment cache
choose newest schema by schema version when compaction (#182)
[bugfix](schema change) fix ligth schema change problem.
[feature](schema change) light schema change add alter job. (#1)
fix be ut
[bug] (schema change) unique drop key column should not light schema
change
[feature](schema change) add schema change regression-test.
fix regression test
[bugfix](schema change) fix multi alter clauses for light schema change. (#2)
[bugfix](schema change) fix multi clauses calculate column unique id (#3)
modify PushTask process (#217)
[Bugfix](schema change) fix jobId replay cause bdbje exception.
[bug](schema change) fix max col unique id repeatitive. (#232)
[optimize](schema change) modify pendingMaxColUniqueId generate rule.
fix compaction error
* fix be ut
* fix snapshot load core
fix unique_id error (#278)
[refact](fe) remove redundant code for light schema change. (#4)
[refact](fe) remove redundant code for light schema change. (#4)
format fe core
format be core
fix be ut
modify fe meta version
fix rebase error
flush schema into rowset_meta in old table
[refactor](schema change) refact fe light schema change. (#5)
delete the change of schemahash and support get max version schema
* modify for review
* fix be ut
* fix schema change test
This PR supports rowset level data upload on the BE side, so that there can be both cold data and hot data in a tablet,
and there is no necessary to prohibit loading new data to cooled tablets.
Each rowset is bound to a `FileSystem`, so that the storage layer can read and write rowsets without
perceiving the underlying filesystem.
The abstracted `RemoteFileSystem` can try local caching strategies with different granularity,
instead of caching segment files as before.
To avoid conflicts with the code in be/src/io, we temporarily put the file system related code in the be/src/io/fs directory.
In the future, `FileReader`s and `FileWriter`s should be unified.
1. Provide a FE conf to test the reliability in single replica case when tablet scheduling are frequent.
2. According to #6063, almost apply this fix on current code.
1. Add TStorageMigrationReqV2 and EngineStorageMigrationTask to support migration action
2. Change TabletManager::create_tablet() for remote storage
3. Change TabletManager::try_delete_unused_tablet_path() for remote storage
This is part of the array type support and has not been fully completed.
The following functions are implemented
1. fe array type support and implementation of array function, support array syntax analysis and planning
2. Support import array type data through insert into
3. Support select array type data
4. Only the array type is supported on the value lie of the duplicate table
this pr merge some code from #4655#4650#4644#4643#4623#2979
* [doris-1008] support backup and restore directly to cloud storage via aws s3 protocol
* Internal][S3DirectAccess] Support backup,restore,load,export directlyconnect to s3
1. Support load and export data from/to s3 directly.
2. Add a config to auto convert broker access to s3 acces when available
Change-Id: Iac96d4b3670776708bc96a119ff491db8cb4cde7
(cherry picked from commit 2f03832ca52221cc7436069b96c45c48c4bc7201)
* [Internal][S3DirectAccess] File path glob compatible with broker
Change-Id: Ie55e07a547aa22c6fa8d432ca926216c10384e68
(cherry picked from commit d4fb25544c0dc06d23e1ada571ec3f8edd4ba56f)
* [internal] [doris-1008] fix log4j class not found
Change-Id: I468176aca0d821383c74ee658d461aba9e7d5be3
(cherry picked from commit 029adaa9d6ded8503acbd6644c1519456f3db232)
* add poms
Co-authored-by: yangzhengguo01 <yangzhengguo01@baidu.com>
In version 0.13, we support a more efficient compaction logic.
This logic will maintain multiple version paths of the tablet.
This can avoid -230 errors and can also support incremental clone.
But the previous incremental clone uses the incremental rowset meta recorded in `incr_rs_meta`.
At present, the incremental rowset meta recorded in `incr_rs_meta` and the records
in `stale_rs_meta` are duplicated, and the current clone logic does not adapt to the
new multi-version path, resulting in many cases not triggering incremental clone.
This CL mainly modified:
1. Removed `incr_rs_meta` metadata
2. Modified the clone logic. When the clone is incremented, it will try to read the rowset in `stale_rs_meta`.
3. Delete a lot of code that was previously used for version compatibility.
This CL refactor the storage medium migration task process in BE.
I did not modify the execution logic. Just extract part of the logic
in the migration task and put it in task_work_pool.
In this way, the migration task is only used to process the migration
from the specified tablet to the specified data dir.
Later, we can use this task to migrate of tablets between different disks. #4476
* Implements the grammar of the batch delete #4051
* Process create, alter table when table has delete sign column
* Support the syntax for enabling the delete column
* Automatically filtered deleted data in the select statement.
* Automatically add delete sign when create rollup table
TODO:
* Optimize the reading and compaction logic on the be side, so that the data marked as deleted will be completely deleted during base compaction
+ Building the materialized view function for schema_change here based on defineExpr.
+ This is a trick because the current storage layer does not support expression evaluation.
+ count distinct materialized view will set mv_expr with to_bitmap or hll_hash.
+ count materialized view will set mv_expr with count.
+ Support to regenerate historical data when a new materialized view is created in BE。
+ Support to_bitmap function
+ Support hll_hash function
+ Support count(field) function
For #3344
