When file cache enabled, running the same query for the second time may be still slow, for `FE` will assign the same
scan range into different backends among different queries, and the former cached data in `BE` will be useless if the scan range is changed.
So, this PR introduce consistent hash to assign the same scan range into the same backend among different queries.
multiget_data working in bthread and may block the whole worker pthread of BRPC framework and effect other bthreads, so I seperate work task into a seperate task pool.
when pg table have some unsupported column type like: point, polygon, jsonb......
jdbc catalog will convert it to string type in doris. but get result set in java is org.postgresql.util.PGobject
Some test need this pr: #16442
1. add limit threshold for topn runtime pushdown and key topn optimization
2. use unified session variable topn_opt_limit_threshold for all topn optimizations
3. add fuzzy support for topn_opt_limit_threshold
change implement of auth to rbac
each user has one default role which can not be drop;
if you grant priv to user,it will grant to default role ,
In the current pr, the user can still only have one role other than the default role, but in the future, the user and role will be many-to-many
rename PaloRole,PaloAuth,PaloPrivilege to Role,Auth,Privilege
The new Nereids planner do column projection after creating scan node. For ExternalFileScanNode, this may cause the columns in required_slots mismatch with the slots after projection. This pr is to reset the required_slots after projection.
This commit support:
1、Insert + select for struct/map type
2、Json stream load for struct type
3、m[key] function for map type
How to use:
Set the fe config to create table for struct and map type
1、admin set frontend config("enable_struct_type" = "true");
2、admin set frontend config("enable_map_type" = "true");
#16547
Co-authored-by: xy720 <xuyang25@baidu.com>
Co-authored-by: amory <wangqiannan@selectdb.com>
Co-authored-by: cambyzju <zhuxiaoli01@baidu.com>
Co-authored-by: hucheng01 <hucheng01@baidu.com>
There were cooldownttl and cooldownttlms in StoragePolicy, it's so error-prone because they served nearly the same.
For example, the init function would only assign the ttl timestamp to cooldownttl, which would end up pushing cooldownttl 0 to be.
Currently, for broadcast shuffle, we serialize a block once and then send it by RPC through multiple channel. After this, we will serialize next block in the same memory for consideration of memory reuse. However, since the RPC is asynchronized, maybe the next block serialization will happen before sending the previous block.
So, in this PR, I use a ref count to identify if the serialized block can be reuse in broadcast shuffle.
`CachedRemoteFileReader` has used fixed segment size(file_cache_max_file_segment_size=4M) to cache remote file blocks. However, the column size in a rowgroup/strip maybe smaller than 10K if a parquet/orc file has many columns, resulting in particularly serious read amplification. For example:
Q1 in clickbench: select count(*) from hits
```
- FileCache: 0ns
- IOHitCacheNum: 552
- IOTotalNum: 835
- ReadFromFileCacheBytes: 19.98 MB
- ReadFromWriteCacheBytes: 0.00
- ReadTotalBytes: 29.52 MB
- SkipCacheBytes: 0.00
- WriteInFileCacheBytes: 915.77 MB
- WriteInFileCacheNum: 283
```
Only 30MB of data is needed, but 900MB+ of data is read from hdfs. The query time of Q1(single scan thread) increased from **5.17s** to **24.45s** when enable file cache.
Therefore, this PR introduce dynamic segment size which is based on the `read_size` of the data. In order to prevent too small or too large IO, the segment size is limited in [4096, file_cache_max_file_segment_size].
Q1 in clickbench is **5.66s** when enable file cache. The performance is almost the same as if the cache is disabled, and the data size read from hdfs is reduced to 45MB.
```
- FileCache: 0ns
- IOHitCacheNum: 297
- IOTotalNum: 835
- ReadFromFileCacheBytes: 8.73 MB
- ReadFromWriteCacheBytes: 0.00
- ReadTotalBytes: 29.52 MB
- SkipCacheBytes: 0.00
- WriteInFileCacheBytes: 45.66 MB
- WriteInFileCacheNum: 544
```
## Remaining Problems
Small queries may result in a large number of small files(4KB at least), and the `BE` saves too much meta information of cached segments.
## Fix bug
`FileCachePolicy` in `FileReaderOptions` is a constant reference, but the parameter passed in `FileFactory::create_file_reader` is a temporary variable, resulting in segmentation fault.
There is something wrong with the `test_broker_load` suite(s3 auth problem).
So I ignore this case temporarily.
cc @wsjz , please help to solve it and add it back
When JDBC client enable server side prepared statement, it will cache OlapScanNode and reuse it for performance, but each
time call `addScanRangeLocations` will add new item to `bucketSeq2locations`, so the `bucketSeq2locations` lead to a memleak if OlapScanNode
cached in memory
make rows_read correct so that the scheduler could using this correctly.
use single scanner if has limit clause. Move it from fragment context to scannode.
---------
Co-authored-by: yiguolei <yiguolei@gmail.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
In vertical base compaction, same rows will be filtered in vertical_merge_iterator,
we should skip these filtered rows when set agg flag of delete sign.
For example, schema is a,b,delete_sign, and data is
1,1,1
1,1,0
1,1,0
2,2,1
2,2
and Block we get in VerticalBlockReader is
1,1,1
2,2,1
and we should set agg flag idex 0,4 to true when handle delete sign, so
we add a function continuous_agg_count to skip same rows filtered in
VerticalMergeIterator.
