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
This pr does three things:
1. add `delete_existing_files` property for outfile/export. If `delete_existing_files = true`, export/outfile will delete all files under file_path first.
2. add p2 test for export
3. modify docs
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.
This work is in the early stage, current progress is not accurate because the scan range will be too large
for gathering information, what's more, only file scan node and import job support new progress manager
## How it works
for example, when we use the following load query:
```
LOAD LABEL test_broker_load
(
DATA INFILE("XXX")
INTO TABLE `XXX`
......
)
```
Initial Progress: the query will call `BrokerLoadJob` to create job, then `coordinator` is called to calculate scan range and its location.
Update Progress: BE will report runtime_state to FE and FE update progress status according to jobID and fragmentID
we can use `show load` to see the progress
PENDING:
```
State: PENDING
Progress: 0.00%
```
LOADING:
```
State: LOADING
Progress: 14.29% (1/7)
```
FINISH:
```
State: FINISHED
Progress: 100.00% (7/7)
```
At current time, full output of `show load\G` looks like:
```
*************************** 1. row ***************************
JobId: 25052
Label: test_broker
State: LOADING
Progress: 0.00% (0/7)
Type: BROKER
EtlInfo: NULL
TaskInfo: cluster:N/A; timeout(s):250000; max_filter_ratio:0.0
ErrorMsg: NULL
CreateTime: 2023-05-03 20:53:13
EtlStartTime: 2023-05-03 20:53:15
EtlFinishTime: 2023-05-03 20:53:15
LoadStartTime: 2023-05-03 20:53:15
LoadFinishTime: NULL
URL: NULL
JobDetails: {"Unfinished backends":{"5a9a3ecd203049bc-85e39a765c043228":[10080]},"ScannedRows":39611808,"TaskNumber":1,"LoadBytes":7398908902,"All backends":{"5a9a3ecd203049bc-85e39a765c043228":[10080]},"FileNumber":1,"FileSize":7895697364}
TransactionId: 14015
ErrorTablets: {}
User: root
Comment:
```
## TODO:
1. The current partition granularity of scan range is too large, resulting in an uneven loading process for progress."
2. Only broker load supports the new Progress Manager, support progress for other query
The original method signature is Block VExprContext::get_output_block_after_execute_exprs(
const std::vectorvectorized::VExprContext*& output_vexpr_ctxs, const Block& input_block,
Status& status)
It return error status as a out parameter and the block as return value. It has to check the block.rows == 0 and then check error status.
It is not conforming to the convention.
---------
Co-authored-by: yiguolei <yiguolei@gmail.com>
Add file cache metrics and management.
1. Get file cache metrics
> If the performance of file cache is not efficient, there are currently no metrics to investigate the cause. In practice, hit ratio, disk usage, and segments removed status are very important information.
API: `http://be_host:be_webserver_port/metrics`
File cache metrics for each base path start with `doris_be_file_cache_` prefix. `hits_ratio` is the hit ratio of the cache since BE startup; `removed_elements` is the num of removed segment files since BE startup; Every cache path has three queues: index, normal and disposable. The capacity ratio of the three queues is 1:17:2.
```
doris_be_file_cache_hits_ratio{path="/mnt/datadisk1/gaoxin/file_cache"} 0.500000
doris_be_file_cache_hits_ratio{path="/mnt/datadisk1/gaoxin/small_file_cache"} 0.500000
doris_be_file_cache_removed_elements{path="/mnt/datadisk1/gaoxin/file_cache"} 0
doris_be_file_cache_removed_elements{path="/mnt/datadisk1/gaoxin/small_file_cache"} 0
doris_be_file_cache_normal_queue_max_size{path="/mnt/datadisk1/gaoxin/file_cache"} 912680550400
doris_be_file_cache_normal_queue_max_size{path="/mnt/datadisk1/gaoxin/small_file_cache"} 8500000000
doris_be_file_cache_normal_queue_max_elements{path="/mnt/datadisk1/gaoxin/file_cache"} 217600
doris_be_file_cache_normal_queue_max_elements{path="/mnt/datadisk1/gaoxin/small_file_cache"} 102400
doris_be_file_cache_normal_queue_curr_size{path="/mnt/datadisk1/gaoxin/file_cache"} 14129846
doris_be_file_cache_normal_queue_curr_size{path="/mnt/datadisk1/gaoxin/small_file_cache"} 14874904
doris_be_file_cache_normal_queue_curr_elements{path="/mnt/datadisk1/gaoxin/file_cache"} 18
doris_be_file_cache_normal_queue_curr_elements{path="/mnt/datadisk1/gaoxin/small_file_cache"} 22
...
```
2. Release file cache
> Frequent segment files swapping can seriously affect the performance of file cache. Adding a deletion interface helps users clean up the file cache.
API: `http://be_host:be_webserver_port/api/file_cache?op=release&base_path=${file_cache_base_path}`
Return the number of released segment files. If `base_path` is not provide in url, all cache paths will be released.
It's thread-safe to call this api, so only the segment files not been read currently can be released.
```
{"released_elements":22}
```
3. Specify the base path to store cache data
> Currently, regression testing lacks test cases of file cache, which cannot guarantee the stability of file cache. This interface is generally used in regression testing scenarios. Different queries use different paths to verify different usage cases and performance.
User can set session variable `file_cache_base_path` to specify the base path to store cache data. `file_cache_base_path="random"` as default, means chosing a random path from cached paths to store cache data. If `file_cache_base_path` is not one of the base paths in BE configuration, a random path is used.
Co-authored-by: yiguolei <yiguolei@gmail.com>
Currently, exec node save exprcontext**, but the object is in object pool, the code is very unclear. we could just use exprcontext*.
Sometimes the dict is not initialized when run comparison predicate here, for example, the full page is null, then the reader will skip read, so that the dictionary is not inited. The cached code is wrong during this case, because the following page maybe not null, and the dict should have items in the future.
This will result the dict string column query return wrong result, if there are many null values in the column.
I also add some regression test for dict column's equal query, larger than query, less than query.
---------
Co-authored-by: yiguolei <yiguolei@gmail.com>
Using both `MergeRangeFileReader` and `BufferedStreamReader` simultaneously would waste a lot of memory,
so turn off prefetch data in `BufferedStreamReader` when using MergeRangeFileReader.
Issue Number: About #19038, we found in this case, l_orderkey has many nulls,
so we can filter it by null count statistics in the row group and page level,
then it can improve a lot of performance in this case.
