When reading to the end of the segment file, clearing the block did not release the memory, leading to high memory usage during compaction.
When reading through segment file for columns that are dictionary encoded, the column iterator in the segment iterator will hold the dictionary. Release the segment iterator to free up the dictionary.
before the agg_state type only support with datatype string,
But with some agg functions, eg: avg,sum,mix...
those functions need serialize type is fixed length object type
1. make ColumnObject exception safe
2. introduce FlushContext and construct schema at memtable flush stage to make segment independent from dynamic schema
3. add more test cases
* [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
Refactoring the filtering conditions in the current ExecNode from an expression tree to an array can simplify the process of adding runtime filters. It eliminates the need for complex merge operations and removes the requirement for the frontend to combine expressions into a single entity.
By representing the filtering conditions as an array, each condition can be treated individually, making it easier to add runtime filters without the need for complex merging logic. The array can store the individual conditions, and the runtime filter logic can iterate through the array to apply the filters as needed.
This refactoring simplifies the codebase, improves readability, and reduces the complexity associated with handling filtering conditions and adding runtime filters. It separates the conditions into discrete entities, enabling more straightforward manipulation and management within the execution node.
/home/zcp/repo_center/doris_master/doris/be/src/olap/rowset/segment_v2/column_reader.cpp:895:21: runtime error: load of value 423208544, which is not a valid value for type 'doris::ReaderType'
/home/zcp/repo_center/doris_master/doris/be/src/vec/columns/column_decimal.cpp:260:33: runtime error: load of misaligned address 0x7fa3348b301c for type 'int64_t' (aka 'long'), which requires 8 byte alignment
/home/zcp/repo_center/doris_master/doris/be/src/olap/block_column_predicate.cpp:82:24: runtime error: variable length array bound evaluates to non-positive value 0
/home/zcp/repo_center/doris_master/doris/be/src/vec/columns/column_string.h:225:26: runtime error: null pointer passed as argument 2, which is declared to never be null
Currently, there are some useless includes in the codebase. We can use a tool named include-what-you-use to optimize these includes. By using a strict include-what-you-use policy, we can get lots of benefits from it.
The offset of _nullmap and _value are inconsistent in OlapDataConvertor, so the obtained null flag is incorrect when calling get_ data_ at function. When the key column or sequence column has null values, the encoding of the short key index or primary key index may be wrong.
This was introduced by #10883#10925.
Arena can replace MemPool in most scenarios. Except for memory reuse, MemPool supports reuse of previous memory chunks after clear, but Arena does not.
Some comparisons between MemPool and Arena:
1. Expansion
Arena is less than 128M index 2 alloc chunk; more than 128M memory, allocate 128M * n > `size`, n is equal to the minimum value that satisfies the expression;
MemPool less than 512K index 2 alloc chunk, greater than 512K memory, separately apply for a `size` length chunk
After Arena applied for a chunk larger than 128M last time, the minimum chunk applied for after that is 128M. Does this seem to be a waste of memory? MemPool is also similar. After the chunk of 512K was applied for last time, the minimum chunk of subsequent applications is 512K.
2. Alignment
MemPool defaults to 16 alignment, because memtable and other places that use int128 require 16 alignment;
Arena has no default alignment;
3. Memory reuse
Arena only supports `rollback`, which reuses the memory of the current chunk, usually the memory requested last time.
MemPool supports clear(), all chunks can be reused; or call ReturnPartialAllocation() to roll back the last requested memory; if the last chunk has no memory, search for the most free chunk for allocation
4. Realloc
Arena supports realloc contiguous memory; it also supports realloc contiguous memory from any position at the time of the last allocation. The difference between `alloc_continue` and `realloc` is:
1. Alloc_continue does not need to specify the old size, but the default old size = head->pos - range_start
2. alloc_continue supports expansion from range_start when additional_bytes is between head and pos, which is equivalent to reusing a part of memory, while realloc completely allocates a new memory
MemPool does not support realloc, but supports transferring or absorbing chunks between two MemPools
5. check mem limit
MemPool checks the mem limit, and Arena checks at the Allocator layer.
6. Support for ASAN
Arena does something extra
7. Error handling
MemPool supports returning the error message of application failure directly through `Status`, and Arena throws Exception.
Tests that Arena can consider
1. After the last applied chunk is larger than 128M, the minimum applied chunk is 128M, which seems to waste memory;
2. Support clear, memory multiplexing;
3. Increase the large list, alloc the memory larger than 128M, and the size is equal to `size`, so as to avoid the current chunk not being fully used, which is wasteful.
4. In some cases, it may be possible to allocate backwards to find chunks t
In the case of rowets non-overlap and desc sorting, the logic of VCollectIterator::Level0Iterator::init_for_union will be followed. In this function, the row ref pos of the first level0 iterator is set to 0, and the row pos of other level0 iterators are all Set to -1.
But in the level1iterator, when rowets are non-overlapping and is ordering by desc, the list of rowset iterators will be reversed, causing the row ref pos of the first level0 iterator in the list to be -1, causing the block reader to think that the entire tablet has no data.
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.
When compaction case, memory map offsets coming to same olap convertor which is from 0 to 0+size
but it should be continue in different pages when in one segment writer .
eg :
last block with map offset : [3, 6, 8, ... 100]
this block with map offset : [5, 10, 15 ..., 100]
the same convertor should record last offset to make later coming offset followed last offset.
so after convertor :
the current offset should [105, 110, 115, ... 200], then column writer just call append_data() to make the right offset data append pages
* [Feature](vectorized)(quantile_state): support vectorized quantile state functions
1. now quantile column only support not nullable
2. add up some regression test cases
3. set default enable_quantile_state_type = true
---------
Co-authored-by: spaces-x <weixiang06@meituan.com>
This patchset applies the following changes:
using vertical compaction machanism to do segcompaction
basic (WIP) refraction to separate segcompaction logic from BetaRowsetWriter
add segcompaction specific ut and regression tests
Sense io error.
Retry query when io error.
Greylist: When finds one disk is completely broken, or the diff of tablet number in BE and FE meta is too large,reduce the query priority of the BE.
