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`
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.
- 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.
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
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*.
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.
Fix tow bugs:
1. Enabling file caching requires both `FE session` and `BE` configurations(enable_file_cache=true) to be enabled.
2. `ParquetReader` has not used `IOContext` previously, but `CachedRemoteFileReader::read_at` needs `IOContext` after PR(#17586).
Problem:
1. FE will split the parquet file into split. So a file can have several splits.
2. BE will scan each split, read the footer of the parquet file.
3. If 2 splits belongs to a same parquet file, the footer of this file will be read twice.
This PR mainly changes:
1. Use kv cache to cache the footer of parquet file.
2. The kv cache is belong to a scan node, so all parquet reader belong to this scan node will share same kv cache.
3. In cache, the key is "meta_file_path", the value is parsed thrift footer.
The KV Cache is sharded into mutlti sub cache.
So that different file can use different sub cache, avoid blocking each other
In my test, a query with 26 splits can reduce the footer parse time from 4s -> 1s
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.
There are many type definitions in BE. Should unify the type system and simplify the development.
---------
Co-authored-by: yiguolei <yiguolei@gmail.com>
1. introduce a new type `VARIANT` to encapsulate dynamic generated columns for hidding the detail of types and names of newly generated columns
2. introduce a new expression `SchemaChangeExpr` for doing schema change for extensibility
The _src_block_mem_reuse variable actually not work, since the _src_block is cleared each time when we call get_block.
But current code may cause core dump, see issue #17587. Because we insert some result column generated by expr into dest block, and such a column holds a pointer to some column in original schema. When clearing the data of _src_block, some column's data in dest block is also cleared.
e.g. coalesce will return a result column which holds a pointer to some original column, see issue #17588
remove duplicate type definition in function context
remove unused method in function context
not need stale state in vexpr context because vexpr is stateless and function context saves state and they are cloned.
remove useless slot_size in all tuple or slot descriptor.
remove doris_udf namespace, it is useless.
remove some unused macro definitions.
init v_conjuncts in vscanner, not need write the same code in every scanner.
using unique ptr to manage function context since it could only belong to a single expr context.
Issue Number: close #xxx
---------
Co-authored-by: yiguolei <yiguolei@gmail.com>
In previous implementation, when querying tvf, FE will get schema from BE.
And BE will try to open the first file to get its schema info, but for orc or parquet format,
if the file is empty, it will return error.
But even for an empty file, we can still get schema info from file's footer.
So we should handle the empty file to get schema info correctly.
Also modify the catalog doc to add some FAQ.
Issue Number: close#16351
Dynamic schema table is a special type of table, it's schema change with loading procedure.Now we implemented this feature mainly for semi-structure data such as JSON, since JSON is schema self-described we could extract schema info from the original documents and inference the final type infomation.This speical table could reduce manual schema change operation and easily import semi-structure data and extends it's schema automatically.
Support iceberg schema evolution for parquet file format.
Iceberg use unique id for each column to support schema evolution.
To support this feature in Doris, FE side need to get the current column id for each column and send the ids to be side.
Be read column id from parquet key_value_metadata, set the changed column name in Block to match the name in parquet file before reading data. And set the name back after reading data.
The origin scan pools are in exec_env.
But after enable new_load_scan_node by default, the scan pool in exec_env is no longer used.
All scan task will be submitted to the scan pool in scanner_scheduler.
BTW, reorganize the scan pool into 3 kinds:
local scan pool
For olap scan node
remote scan pool
For file scan node
limited scan pool
For query which set cpu resource limit or with small limit clause
TODO:
Use bthread to unify all IO task.
Some trivial issues:
fix bug that the memtable flush size printed in log is not right
Add RuntimeProfile param in VScanner
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>
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.
**Optimize**
PR #14470 has used `Expr` to filter delete rows to match current data file,
but the rows in the delete file are [sorted by file_path then position](https://iceberg.apache.org/spec/#position-delete-files)
to optimize filtering rows while scanning, so this PR remove `Expr` and use binary search to filter delete rows.
In addition, delete files are likely to be encoded in dictionary, it's time-consuming to decode `file_path`
columns into `ColumnString`, so this PR use `ColumnDictionary` to read `file_path` column.
After testing, the performance of iceberg v2's MOR is improved by 30%+.
**Fix Bug**
Lazy-read-block may not have the filter column, if the whole group is filtered by `Expr`
and the batch_eof is generated from next batch.
Current column default value is used only for load task. But in the case of Iceberg schema change,
query task is also possible to read the default value for columns not exist in old schema.
This pr is to support default value for query task.
Manually tested the broker load and external emr regression cases.
Fix three bugs:
1. DataTypeFactory::create_data_type is missing the conversion of binary type, and OrcReader will failed
2. ScalarType#createType is missing the conversion of binary type, and ExternalFileTableValuedFunction will failed
3. fmt::format can't generate right format string, and will be failed
Set FE `enable_new_load_scan_node` to true by default.
So that all load tasks(broker load, stream load, routine load, insert into) will use FileScanNode instead of BrokerScanNode
to read data
1. Support loading parquet file in stream load with new load scan node.
2. Fix bug that new parquet reader can not read column without logical or converted type.
3. Change jsonb parser function to "jsonb_parse_error_to_null"
So that if the input string is not a valid json string, it will return null for jsonb column in load task.
FE file path cache for external table may out of date. In this case, BE may fail to find the not exist file from FE cache.
This pr is to handle this case: instead of throw an error message to the user, we return empty result set to the user.
1. a icebergv2 delete file may cross many data paths, so the path of a file split is required as a predicate to filter rows of delete file
- create delete file structure to save predicate parameters
- create predicate for file path
2. add some log to print row range
3. fix bug when create file metadata
json reader DCHECK fail because of missing TYPE_STRING
fix bug that if no file is found, the tvf will throw NPE.
The predicate conjuncts can not be pushed down to parquet reader if this is a load task.
Because the predicate should be applied on column of dest table, not on column of source file.
Add a temp property "use_new_load_scan_node" of broker load to make regression test happy.
So that we can use new load scan node for a certain job and avoid setting global FE config.
PR https://github.com/apache/doris/pull/13917 has supported lazy read for non-predicate columns in ParquetReader,
but can't trigger lazy read when predicate columns are partition or missing columns.
This PR support such case, and fill partition and missing columns in `FileReader`.
Read predicate columns firstly, and use VExprContext(push-down predicates)
to generate the select vector, which is then applied to read the non-predicate columns.
The data in non-predicate columns may be skipped by select vector, so the value-decode-time can be reduced.
If a whole page can be skipped, the decompress-time can also be reduced.
Support running transactional insert operation with new scan framework. eg:
admin set frontend config("enable_new_load_scan_node" = "true");
begin;
insert into tbl1 values(1,2);
insert into tbl1 values(3,4);
insert into tbl1 values(5,6);
commit;
Add some limitation to transactional insert
Do not support non-literal value in insert stmt
Fix some issue about array type:
Forbid cast other non-array type to NESTED array type, it may cause BE crash.
Add getStringValueForArray() method for Expr, to get valid string-formatted array type value.
Add useLocalSessionState=true in regression-test jdbc url
without this config, the jdbc driver will send some init cmd each time it connect to server, such as
select @@session.tx_read_only.
But when we use transactional insert, after begin command, Doris do not support any other type of
stmt except for insert, commit or rollback.
So adding this config to let the jdbc NOT send cmd when connecting.
Issue Number: close#12574
This pr adds `NewJsonReader` which implements GenericReader interface to support read json format file.
TODO:
1. modify `_scann_eof` later.
2. Rename `NewJsonReader` to `JsonReader` when `JsonReader` is deleted.
The index for external table columns from path is incorrect in new scanner. This is a fix for it.
e.g. In the next query, nation and city columns are from path
```
mysql> select nation, city, count(*) from parquet_two_part group by nation, city;
+--------+------------+----------+
| nation | city | count(*) |
+--------+------------+----------+
| cn | beijing | 1199969 |
| cn | shanghai | 1199771 |
| jp | tokyo | 599715 |
| rus | moscow | 600659 |
| us | chicago | 1199805 |
| us | washington | 1201296 |
+--------+------------+----------+
6 rows in set (0.39 sec)
```
1. Missing field and line delimiter
2. When query external table with text(csv) format, we should pass the column position map to BE,
otherwise the column order is wrong.
TODO:
1. For now, if we query csv file with non-exist column, it will return null.
But it should return null or default value of that column.
2. Add regression test after hive docker is ready.
1. remove FE config `enable_array_type`
2. limit the nested depth of array in FE side.
3. Fix bug that when loading array from parquet, the decimal type is treated as bigint
4. Fix loading array from csv(vec-engine), handle null and "null"
5. Change the csv array loading behavior, if the array string format is invalid in csv, it will be converted to null.
6. Remove `check_array_format()`, because it's logic is wrong and meaningless
7. Add stream load csv test cases and more parquet broker load tests
1. Refactor the file reader creation in FileFactory, for simplicity.
Previously, FileFactory had too many `create_file_reader` interfaces.
Now unified into two categories: the interface used by the previous BrokerScanNode,
and the interface used by the new FileScanNode.
And separate the creation methods of readers that read `StreamLoadPipe` and other readers that read files.
2. Modify the StreamLoadPlanner on FE side to support using ExternalFileScanNode
3. Now for generic reader, the file reader will be created inside the reader, not passed from the outside.
4. Add some test cases for csv stream load, the behavior is same as the old broker scanner.
Fix some logic about broker load using new file scanner, with parquet format:
1. If columns are specified in load stmt, but none of them are in parquet file,
error will be thrown like `err: No columns found in file`. See `parquet_s3_case4`
2. If the first column of table are not in table, the result number of rows is wrong.
See `parquet_s3_case8`
3. If column specified in `columns` in load stmt does not exist in file and table,
error will be thrown like: `failed to find default value expr for slot: x1`. See `parquet_s3_case2`
