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
```
Parallel scanning can result in some read amplification, for example, select * from xx where limit 1 actually requires only one row of data. However, due to parallel scanning of multiple tablets, read amplification occurs, leading to performance bottlenecks in high-concurrency scenarios. This PR Adding a SessionVariable to enforce serial scanning can help mitigate this issue.
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
This PR refactors the old way of writing data to JDBC External Table & JDBC Catalog, mainly including the following tasks
1. Continuing the work of @BePPPower 's PR #18594, changing the logic of splicing Inster sql to operating off-heap memory and using preparedStatement.set to write data logic to complete
2. Supplement the support written by largeint type, mainly to adapt to Java.Math.BigInteger, which uses binary operations
3. Delete the splicing SQL logic in the JDBC External Table & JDBC Catalog related written code
ToDo: Binary type，like bit,binary, blob...
Finally, special thanks to @BePPPower , @AshinGau for his work
Co-authored-by: Tiewei Fang <43782773+BePPPower@users.noreply.github.com>
1. Fix create catalog with resource replay bug.
If user create catalog using `create catalog hive with resource xxx`, when replaying edit log,
there is a bug that resource may be dropped, causing NPE and FE will fail to start.
In this PR, I add a new FE config `disallow_create_catalog_with_resource`, default is true.
So that `with resource` will not be allowed, and it will be deprecated later.
And also fix the replay bug to avoid NPE.
2. Fix issue when creating 2 hive catalogs to connect with and without kerberos authentication.
When user create 2 hive catalogs, one use simple auth, the other use kerberos auth.
The query may fail with error like: `Server asks us to fall back to SIMPLE auth, but this client is configured to only allow secure connections.`
So I add a default property for hive catalog: `"ipc.client.fallback-to-simple-auth-allowed" = "true"`.
Which means this property will be added automatically when user creating hive catalog, to avoid such problem.
3. Fix calling `hdfsExists()` issue
When calling `hdfsExists()` with non-zero return code, should check if it encounters error or is file not found.
3. Some code refactor
Avoid import `org.apache.parquet.Strings`
* [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.
before: the node will wait to retrieve all data from child, then send data to parent.
now: for data from child that does not require sorting, it can be sent to parent immediately.
#18976 introduced merge small IO facility to optimize performance, and used by parquet reader.
This PR support this facility in orc reader. Current ORC reader implementation need to reposition parent present stream when reading lazy columns in lazy materialization facility. So let it works by removing `DCHECK_GE(offset, cached_data.end_offset)`.
/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
Firstly, to reduce memory usage, we do not pre-allocate blocks, instead we lazily allocate block when upper call get_free_block. And when upper call return_free_block to return free block, we add the block to a queue for memory reuse, and we will free the blocks in the queue when the scanner_context was closed instead of destructed.
Secondly, to limit the memory usage of the scanner, we introduce a variable _free_blocks_capacity to indicate the current number of free blocks available to the scanners. The number of scanners that can be scheduled will be calculated based on this value.
ssb flat test
previous
lineorder 1.2G:
load time: 3s, query time: 0.355s
lineorder 5.8G:
load time: 330s, query time: 0.970s
load time: 349s, query time: 0.949s
load time: 349s, query time: 0.955s
load time: 360s, query time: 0.889s (pipeline enabled)
after
lineorder 1.2G:
load time: 3s, query time: 0.349s
lineorder 5.8G:
load time: 342s, query time: 0.929s
load time: 337s, query time: 0.913s
load time: 345s, query time: 0.946s
load time: 346s, query time: 0.865s (pipeline enabled)
Fix partition field conjuncts not work.
Add predicate_partition_columns in _slot_id_to_filter_conjuncts(single slot conjuncts) to _filter_conjuncts, others should had been added from not_single_slot_filter_conjuncts.
Fix threes bugs of timestampv2 precision:
1. Hive catalog doesn't set the precision of timestampv2, and can't get the precision from hive metastore, so set the largest precision for timestampv2;
2. Jdbc catalog use datetimev1 to parse timestamp, and convert to timestampv2, so the precision is lost.
3. TVF doesn't use the precision from meta data of file format.
1. Remove an exec node method corresponding to a span and replace it with an exec node corresponding to a span;
2. Fix some problems with tracing in pipeline.
fix some wrong downcast founded by ubsan.
```cpp
doris/be/src/olap/bloom_filter_predicate.h:43:32: runtime error: downcast of address 0x7f8ec2b691a0 which does not point to an object of type 'doris::BloomFilterColumnPredicate<doris::TYPE_DATE>::SpecificFilter' (aka 'BloomFilterFunc<(doris::PrimitiveType)11U>')
0x7f8ec2b691a0: note: object is of type 'doris::BloomFilterFunc<(doris::PrimitiveType)12>'
e5 55 00 00 10 74 58 42 e5 55 00 00 00 00 10 00 8e 7f 00 00 20 07 6f cc 8e 7f 00 00 80 fe 68 cc
^~~~~~~~~~~~~~~~~~~~~~~
vptr for 'doris::BloomFilterFunc<(doris::PrimitiveType)12>'
```
1. TYPE_DATE/TYPE_DATETIME have same data format, so I change the cast about bloom filter to reinterpret cast.
```cpp
doris/be/src/vec/exec/format/orc/vorc_reader.h:281:17: runtime error: downcast of address 0x7f562f4c3180 which does not point to an object of type 'ColumnVector<int>'
0x7f562f4c3180: note: object is of type 'doris::vectorized::ColumnDecimal<doris::vectorized::Decimal<int> >'
74 65 00 00 20 91 70 f5 ca 55 00 00 02 00 00 00 00 00 00 00 f0 d4 4c 2f 56 7f 00 00 f0 d4 4c 2f
^~~~~~~~~~~~~~~~~~~~~~~
vptr for 'doris::vectorized::ColumnDecimal<doris::vectorized::Decimal<int> >'
```
2. doris use ColumnDecimal to store decimal elements.
1. fix function define of `Retention` inconsist, this function return tinyint on `FE` and return uint8 on `BE`
2. make assert_cast support cast to derived
3. change some static cast to assert cast
4. support sum(bool)/avg(bool)
1.some encrypt and decrypt functions have wrong blockEncryptionMode
2.topN node should compare tuples from intermediate_row_desc with first_sort_slot.tuple_id
3.must keep the limit if it's an uncorrelated in-subquery with limit on sort, like select a from t1 where a in ( select b from t2 order by xx limit yy )
Doris block does not support complex nested type now, but orc and parquet reader has generated complex nested column,
which makes the output of mysql client wrong and users confused.
Get the last modification time from file status, and use the combination of path and modification time to generate cache identifier.
When a file is changed, the modification time will be changed, so the former cache path will be invalid.
- Implements ORC lazy materialization, integrate with the implementation of https://github.com/apache/doris-thirdparty/pull/56 and https://github.com/apache/doris-thirdparty/pull/62.
- Refactor code: Move `execute_conjuncts()` and `execute_conjuncts_and_filter_block()` in `parquet_group_reader `to `VExprContext`, used by parquet reader and orc reader.
- Add session variables `enable_parquet_lazy_materialization` and `enable_orc_lazy_materialization` to control whether enable lazy materialization.
- Modify `build.sh` to update apache-orc submodule or download package every time.
when I use mysql-jdbc 5.1.47 create a doris jdbc catalog, the largeint cannot select
When mysql-jdbc reads largeint, it will convert the format to string because it is too long
mysql> select `largeint` from type3;
ERROR 1105 (HY000): errCode = 2, detailMessage = (127.0.0.1)[INTERNAL_ERROR]Fail to convert jdbc type of java.lang.String to doris type LARGEINT on column: largeint. You need to check this column type between external table and doris table.
Support querying data from the Nebula graph database
This feature comes from the needs of commercial customers who have used Doris and Nebula, hoping to connect these two databases
changes mainly include:
* add New Graph Database JDBC Type
* Adapt the type and map the graph to the Doris type
Fix dict cols not be converted back to string type in some cases, which includes introduced by #19039.
For dict cols, we will convert dict cols to int32 type firstly, then convert back to string type after read block.
The block will be reuse it, so it is necessary to convert it back.
