Describe your changes.
Firstly having clause of Mysql is really very complex, we are hard to follow all rules, so we revert pr15143 to keep the logic the same as before.
Secondly the origin implementation has problem while having clause has multi-conditions.
For example:
case1: here v2 inside having clause use table column test_having_alias_tb.v2
SELECT id, v1-2 as v, sum(v2) v2 FROM test_having_alias_tb GROUP BY id,v having(v2>1);
ERROR 1105 (HY000): errCode = 2, detailMessage = HAVING clause not produced by aggregation output (missing from GROUP BY clause?): (`v2` > 1)
case2: here v2 inside having clause use alias name v2 =sum(test_having_alias_tb.v2), another condition make logic of v2 differently.
SELECT id, v1-2 as v, sum(v2) v2 FROM test_having_alias_tb GROUP BY id,v having(v>0 AND v2>1) ORDER BY id,v;
+------+------+------+
| id | v | v2 |
+------+------+------+
| 2 | 1 | 3 |
+------+------+------+
So here we try to make the having clause rules simple:
Rule1: if alias name inside having clause is the same as column name, we use column name not alias name;
Rule2: if alias name inside having clause do not have same name as column name, we use alias name;
Co-authored-by: cambyzju <zhuxiaoli01@baidu.com>
The main purpose of this pr is to import `fileCache` for lakehouse reading remote files.
Use the local disk as the cache for reading remote file, so the next time this file is read,
the data can be obtained directly from the local disk.
In addition, this pr includes a few other minor changes
Import File Cache:
1. The imported `fileCache` is called `block_file_cache`, which uses lru replacement policy.
2. Implement a new FileRereader `CachedRemoteFilereader`, so that the logic of `file cache` is hidden under `CachedRemoteFilereader`.
Other changes:
1. Add a new interface `fs()` for `FileReader`.
2. `IOContext` adds some statistical information to count the situation of `FileCache`
Co-authored-by: Lightman <31928846+Lchangliang@users.noreply.github.com>
1. generate lots of aggregate functions
2. support `group_concat(columns order by order_columns)` grammer
3. support and generate array aggregate/scalar functions, like `array_union`. we should support array grammar in the future, e.g. `select [1, 2, 3]`
4. add `checkLegalityBeforeTypeCoercion` and `checkLegalityAfterRewrite` function to check the legality of expression before type coercion and after rewrite, copy the semantic check of `FunctionCallExpr` to the checkLegality; remove the `ForbiddenMetricTypeArguments`; move the check of aes/sm4 crypto function from translator to checkLegalityBeforeTypeCoercion
5. refactor the `NullableAggregateFunction`: distinct is the first parameter, alwaysNullable is the second parameter; Fix some wrong initialize order: some function invoke super(distinct, alwaysNullable) but some function invoke super(alwaysNullable, distinct)
all conjuncts should be added before HashJoinNode init. Otherwise, some slots on conjuncts linked to the tuple not in intermediate tuple on HashJoinNode
For outer join / right outer join / right semi join, when HashJoinNode::pull->process_data_in_hashtable outputs a block, it will output all rows of a key in the hash table into a block, and the output of a key is completed After that, it will check whether the block size exceeds the batch size, and if it exceeds, the output will be terminated.
If a key has 2000w+ rows, memory overflow will occur when the subsequent block operations on the 2000w+ rows are performed.
Tablet::version_for_delete_predicate should travel all rowset metas in tablet meta which complex is O(N), however we can directly judge whether this rowset is a delete rowset by RowsetMeta::has_delete_predicate which complex is O(1).
As we won't call Tablet::version_for_delete_predicate when pick input rowsets for compaction, we can reduce the critical area of Tablet::_meta_lock.
Though this syntax doesn't get suppoted in many other systems since the order by clause here almost redandunt and useless but we have to keep consistent with the legacy doris syntax
Here is a example:
SELECT * FROM (SELECT k1, k3 FROM tbl1 ORDER BY k3 UNION ALL SELECT k1, k5 FROM tbl2) t;
when need to scan more than one olap table partition and it is not a colocate table or its colocate group is unstable, we need to make it as any distribution even if its distribution type is Hash
Bug fix
fix image loading failture when create catalog with resource
When creating jdbc catalog with resource, the metadata image will failed to be loaded.
Because when loading jdbc catalog image, it will try to get resource from ResourceMgr,
but ResourceMgr has not been loaded, so NPE will be thrown.
This PR fix this bug, and refactor some logic about catalog and resource.
When loading jdbc catalog image, it will not get resource from ResourceMgr.
And now user can create catalog with resource and properties, like:
create catalog jdbc_catalog with resource jdbc_resource
properites("user" = "user1");
The properties in "properties" clause will overwrite the properties in "jdbc_resource".
force adding tinyInt1isBit=false to jdbc url
The default value of tinyInt1isBit is true, and it will cause tinyint in mysql to be bit type.
force adding tinyInt1isBit=false to jdbc url so that the tinyint in mysql will be tinyint in Doris.
Avoid calculate checksum of jdbc driver jar multiple times
Refactor
Refactor the notification logic when updating properties in resource.
When updating properties in resource, it will notify the corresponding catalog to update its own properties.
This PR change this logic. After updating properties in resource, it will only uninitialize the catalog's internal
objects such "jdbc client" or "hms client". And this objects will be re-initialized lazily.
And all properties will be got from Resource at runtime, so that it will always get the latest properties
Regression test cases
Because we add tinyInt1isBit=false to jdbc url, some of cases need to be changed.
Now in ScannerContext::push_back_scanner_and_reschedule, _num_running_scanners-- is before _num_scheduling_ctx++.
InPipScannerContext::can_finish, we check _num_running_scanners == 0 && _num_scheduling_ctx == 0 without obtaining _transfer_lock.
In follow case, PipScannerContext::can_finish will return wrong result.
_num_running_scanners--
Check _num_running_scanners == 0 && _num_scheduling_ctx == 0` return true.
_num_scheduling_ctx++
So, we can set _num_running_scanners-- in the last of this func.
Describe your changes.
PipScannerContext::get_block_from_queue not block.
Set _num_running_scanners-- in the last of ScannerContext::push_back_scanner_and_reschedule.
2. add antd Table Component missing rowKey property to fit react specification
2. fix system/query profile/session/configuration page maybe lead memory leak when switch these pages fast
3.other grammar fix to fit typescript and react specification
Co-authored-by: tongyang.hty <hantongyang@douyu.tv>
* [refactor] delete non vec load from memtable
delete non vec load from memtable totally.
remove function keys_type() in memtable.
Co-authored-by: zhoubintao <1229701101@qq.com>
In old version, NODE_PRIV will be incorrectly assigned to normal users.
So when upgrading to 1.2.x, it will failed to handle this unexpected case.
This PR fix this by removing NODE_PRIV from normal user.
fix a dcheck error for vertical compaction on Merge-On-Write table。
When merge rowsets with empty segment, VerticalHeapMergeIterator::init
return ok directly and _record_rowids not set, dcheck failed when
_unique_key_next_block call current_block_row_locations。
When creating an external catalog, Doris will automatically sync the schema of table from external catalog.
But some of column type are not supported by Doris now, such as struct, map, etc.
In previous, when meeting these unsupported column, Doris will throw an exception, and the corresponding
table can not be synced. But user may just want to query other supported columns.
In this PR, I add a new column type: UNSUPPORTED. And now it is just used for external table schema sync.
When meeting unsupported column, it will be synced as column with UNSUPPORTED type.
When query this table, there are serval situation:
select * from table: throw error Unsupported type 'UNSUPPORTED_TYPE' xxx
select k1 from table: k1 is with supported type. query OK.
select * except(k2): k2 is with unsupported type. query OK
A deleted file may belong to multiple data files. Each data file will read a full amount of deleted files,
so a deleted file may be read repeatedly. The deleted files can be cached, and multiple data files
can reuse the first read content.
The performance is improved by 60% in the case of single thread, and by 30% in the case of multithreading.
Histogram statistics are more expensive to collect and we collect and persist them separately.
This PR does the following work:
1. Add histogram syntax and add keyword `TABLE`
2. Add the task of collecting histogram statistics
3. Persistent histogram statistics
4. Replace fastjson with gson
5. Add unit tests...
Relevant syntax examples：
> Refer to some databases such as mysql and add the keyword `TABLE`.
```SQL
-- collect column statistics
ANALYZE TABLE statistics_test;
-- collect histogram statistics
ANALYZE TABLE statistics_test UPDATE HISTOGRAM ON col1,col2;
```
base on #15317
This pr mainly to optimize the histogram(👉🏻https://github.com/apache/doris/pull/14910) aggregation function. Including the following:
1. Support input parameters `sample_rate` and `max_bucket_num`
2. Add UT and regression test
3. Add documentation
4. Optimize function implementation logic
Parameter description：
- `sample_rate`：Optional. The proportion of sample data used to generate the histogram. The default is 0.2.
- `max_bucket_num`：Optional. Limit the number of histogram buckets. The default value is 128.
---
Example：
```
MySQL [test]> SELECT histogram(c_float) FROM histogram_test;
+-------------------------------------------------------------------------------------------------------------------------------------+
| histogram(`c_float`) |
+-------------------------------------------------------------------------------------------------------------------------------------+
| {"sample_rate":0.2,"max_bucket_num":128,"bucket_num":3,"buckets":[{"lower":"0.1","upper":"0.1","count":1,"pre_sum":0,"ndv":1},...]} |
+-------------------------------------------------------------------------------------------------------------------------------------+
MySQL [test]> SELECT histogram(c_string, 0.5, 2) FROM histogram_test;
+-------------------------------------------------------------------------------------------------------------------------------------+
| histogram(`c_string`) |
+-------------------------------------------------------------------------------------------------------------------------------------+
| {"sample_rate":0.5,"max_bucket_num":2,"bucket_num":2,"buckets":[{"lower":"str1","upper":"str7","count":4,"pre_sum":0,"ndv":3},...]} |
+-------------------------------------------------------------------------------------------------------------------------------------+
```
Query result description：
```
{
"sample_rate": 0.2,
"max_bucket_num": 128,
"bucket_num": 3,
"buckets": [
{
"lower": "0.1",
"upper": "0.2",
"count": 2,
"pre_sum": 0,
"ndv": 2
},
{
"lower": "0.8",
"upper": "0.9",
"count": 2,
"pre_sum": 2,
"ndv": 2
},
{
"lower": "1.0",
"upper": "1.0",
"count": 2,
"pre_sum": 4,
"ndv": 1
}
]
}
```
Field description：
- sample_rate：Rate of sampling
- max_bucket_num：Limit the maximum number of buckets
- bucket_num：The actual number of buckets
- buckets：All buckets
- lower：Upper bound of the bucket
- upper：Lower bound of the bucket
- count：The number of elements contained in the bucket
- pre_sum：The total number of elements in the front bucket
- ndv：The number of different values in the bucket
> Total number of histogram elements = number of elements in the last bucket(count) + total number of elements in the previous bucket(pre_sum).
