change some parameter's default value:
brpc_num_threads from -1 to 256
compaction_task_num_per_disk from 2 to 4
compaction_task_num_per_fast_disk from 4 to 8
fragment_pool_thread_num_max from 512 to 2048
fragment_pool_queue_size from 2048 to 4096
---------
Co-authored-by: yiguolei <yiguolei@gmail.com>
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
configs
1. Because vertical compaction is enabled by default, it consumes less
memory, we can enlarge default value of compaction related configs.
2. Enlarge default value of shard size related to lock.
configs
Bdbje elect timeout is 30 seconds, so we enlarge thrift_rpc_timeout_ms
and txn_commit_rpc_timeout_ms to 60s.
BTW: enlarge bdbje_lock_timeout_second from 1 to 5.
Use weak_ptr to cache the file handle of file segment. The max cached number of file handles can be configured by `file_cache_max_file_reader_cache_size`, default `1000000`.
Users can inspect the number of cached file handles by request BE metrics: `http://be_host:be_webserver_port/metrics`:
```
# TYPE doris_be_file_cache_segment_reader_cache_size gauge
doris_be_file_cache_segment_reader_cache_size{path="/mnt/datadisk1/gaoxin/file_cache"} 2500
```
Introduce libunwind get stack trace, cost is negligible and has line numbers.
use StackTraceCache, PHDRCache speed up, is customizable and has some optimizations.
Other stack trace tools remain: glog, boost, glibc, in case for need.
TODO:
currently support linux __x86_64__, __arm__, __powerpc__, not supported __FreeBSD__, APPLE
Note: __arm__, __powerpc__ not been verified
Support signal handle
libunwid support unw_backtrace for jemalloc
Use of undefined compile option USE_MUSL for later
Add a new BE config `kerberos_ticket_lifetime_seconds`, default is 86400.
Better set it same as the value of `ticket_lifetime` in `krb5.conf`
If a HDFS fs handle in cache is live longer than HALF of this time, it will be set as invalid and recreated.
And the kerberos ticket will be renewed.
* [Improve](dynamic schema) support filtering invalid data
1. Support dynamic schema to filter illegal data.
2. Expand the regular expression for ColumnName to support more column names.
3. Be compatible with PropertyAnalyzer and support legacy tables.
4. Default disable parse multi dimenssion array, since some bug unresolved
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.
For routine load (kafka load), user can produce all data for different
table into single topic and doris will dispatch them into corresponding
table.
Signed-off-by: freemandealer <freeman.zhang1992@gmail.com>
Optimize the strategy of merging small IO to prevent severe read amplification, and turn off merged IO when file cache enabled.
Adjustable parameters:
```
// the max amplified read ratio when merging small IO
max_amplified_read_ratio=0.8
// the min segment size
file_cache_min_file_segment_size = 1048576
```
Test on SSB 100g:
select lo_suppkey, count(distinct lo_linenumber) from lineorder group by lo_suppkey;
exec time: 4.388s
create materialized view:
create materialized view customer_uv as select lo_suppkey, bitmap_union(to_bitmap(lo_linenumber)) from lineorder group by lo_suppkey;
select lo_suppkey, count(distinct lo_linenumber) from lineorder group by lo_suppkey;
exec time: 12.908s
test with the patch, exec time: 5.790s
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
