If a failure occurs, doris may retry. Due to ctx->is_read_schema is a global variable that has not been reset in a timely manner, which may cause exceptions.
---------
Co-authored-by: yiguolei <676222867@qq.com>
BE will crash because done run twice when try_offer() failed in
request_slave_tablet_pull_rowset.
Signed-off-by: freemandealer <freeman.zhang1992@gmail.com>
Current initialization dependency:
Daemon ───┬──► StorageEngine ──► ExecEnv ──► Disk/Mem/CpuInfo
│
│
BackendService ─┘
However, original code incorrectly initialize Daemon before StorageEngine.
This PR also stop and join threads of daemon services in their dtor, to ensure Daemon services release resources in reverse order of initialization via RAII.
1. do not split compress data file
Some data file in hive is compressed with gzip, deflate, etc.
These kinds of file can not be splitted.
2. Support lz4 block codec
for hive scan node, use lz4 block codec instead of lz4 frame codec
4. Support snappy block codec
For hadoop snappy
5. Optimize the `count(*)` query of csv file
For query like `select count(*) from tbl`, only need to split the line, no need to split the column.
Need to pick to branch-2.0 after this PR: #22304
During offer_failed(), rpc done will be executed so the response will be
sent and released. Further access to such object will cause NPE error.
So let us just return after offer_failed().
This PR was originally #16940 , but it has not been updated for a long time due to the original author @Cai-Yao . At present, we will merge some of the code into the master first.
thanks @Cai-Yao @yiguolei
Default, if less than or equal 32 core, the following are 128, 128, 10240, 10240 in turn.
if greater than 32 core, the following are core num * 4, core num * 4, core num * 320, core num * 320 in turn
brpc_heavy_work_pool_threads
brpc_light_work_pool_threads
brpc_heavy_work_pool_max_queue_size
brpc_light_work_pool_max_queue_size
* [Fix](rowset) When a rowset is cooled down, it is directly deleted. This can result in data query misses in the second phase of a two-phase query.
related pr #20732
There are two reasons for moving the logic of delayed deletion from the Tablet to the StorageEngine. The first reason is to consolidate the logic and unify the delayed operations. The second reason is that delayed garbage collection during queries can cause rowsets to remain in the "stale rowsets" state, preventing the timely deletion of rowset metadata, It may cause rowset metadata too large.
* not use unused rowsets
If there is only one fragment of a query plan, FE will call `exec_plan_fragment` rpc to BE.
And on BE side, the `exec_plan_fragment()` will be executed directly in bthread, but it may call
some JNI method like `AttachCurrentThread()`, which will return error in bthread.
So I modify the `exec_plan_fragment` to make sure it will be executed in pthread pool.
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.
Only switch to bthread local when modifying the mem tracker in the thread context. No longer switches to bthread local by default when bthread starts
mem tracker increases brpc IOBufBlockMemory memory
remove thread mem tracker metrics
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.
* [Improve](performance) introduce SchemaCache to cache TabletSchame & Schema
1. When the system is under high-concurrency load with wide table point queries, the frequent memory allocation and deallocation of Schema become evident system bottlenecks. Additionally, the initialization of TabletSchema and Schema also becomes a CPU hotspot.Therefore, the introduction of a SchemaCache is implemented to cache these resources for reuse.
2. Make some variables wrapped with std::unique<unique_ptr>
Performance:
| 状态 | QPS | 平均响应时间 (avg) | P99 响应时间 |
|------------------|-----|------------------|-------------|
| 开启 SchemaCache | 501 | 20ms | 34ms |
| 关闭 SchemaCache | 321 | 31ms | 61ms |
* handle schema change with schema version
* remove useless header
* rebase
1. Before this PR if rowset does not contain column which should be read for related SlotDescriptor will call `insert_default` to column, but it's not this real defautl value.Real default value relevant information should be provided by the frontend side.
2. Support fetch when light schema change is not enabled, but disable for AGG or UNIQUE MOR model
