* [Optimize] optimize the speed of converting integer to string
* Use fmt and std::from_chars to make convert integer to string and convert string to integer more efficient
Co-authored-by: caiconghui <caiconghui@xiaomi.com>
Use `commitAsync` to commit offset to kafka, instead of using `commitSync`, which may block for a long time.
Also assign a group.id to routine load if user not specified "property.group.id" property, so that all consumer of
this job will use same group.id instead of a random id for each consume task.
## Proposed changes
Add transaction for the operation of insert. It will cost less time than non-transaction(it will cost 1/1000 time) when you want to insert a amount of rows.
### Syntax
```
BEGIN [ WITH LABEL label];
INSERT INTO table_name ...
[COMMIT | ROLLBACK];
```
### Example
commit a transaction:
```
begin;
insert into Tbl values(11, 22, 33);
commit;
```
rollback a transaction:
```
begin;
insert into Tbl values(11, 22, 33);
rollback;
```
commit a transaction with label:
```
begin with label test_label;
insert into Tbl values(11, 22, 33);
commit;
```
### Description
```
begin: begin a transaction, the next insert will execute in the transaction until commit/rollback;
commit: commit the transaction, the data in the transaction will be inserted into the table;
rollback: abort the transaction, nothing will be inserted into the table;
```
### The main realization principle:
```
1. begin a transaction in the session. next sql is executed in the transaction;
2. insert sql will be parser and get the database name and table name, they will be used to select a be and create a pipe to accept data;
3. all inserted values will be sent to the be and write into the pipe;
4. a thread will get the data from the pipe, then write them to disk;
5. commit will complete this transaction and make these data visible;
6. rollback will abort this transaction
```
### Some restrictions on the use of update syntax.
1. Only ```insert``` can be called in a transaction.
2. If something error happened, ```commit``` will not succeed, it will ```rollback``` directly;
3. By default, if part of insert in the transaction is invalid, ```commit``` will only insert the other correct data into the table.
4. If you need ```commit``` return failed when any insert in the transaction is invalid, you need execute ```set enable_insert_strict = true``` before ```begin```.
At present, some constant expression calculations are implemented on the FE side,
but they are incomplete, and some expressions cannot be completely consistent with
the value calculated by BE (such as part of the time function)
Therefore, we provide a way to pass all the constants in SQL to BE for calculation,
and then begin to analyze and plan SQL. This method can also solve the problem that some
complex constant calculations issued by BI cannot be processed on the FE side.
Here through a session variable enable_fold_constant_by_be to control this function,
which is disabled by default.
* Revert "[Optimize] Put _Tuple_ptrs into mempool when RowBatch is initialized (#6036)"
This reverts commit f254870aeb18752a786586ef5d7ccf952b97f895.
* [BUG][Timeout][QueryLeak] Fixed memory not released in time, Fix Core dump in bloomfilter
This is part of the array type support and has not been fully completed.
The following functions are implemented
1. fe array type support and implementation of array function, support array syntax analysis and planning
2. Support import array type data through insert into
3. Support select array type data
4. Only the array type is supported on the value lie of the duplicate table
this pr merge some code from #4655#4650#4644#4643#4623#2979
refactor runtime filter bloomfilter and eliminate some virtual function calls which obtained a performance improvement of about 5%
import block bloom filter, for avx version obtained 40% performance improvement
before: bloomfilter size:default, about 2000W item cost about 1s400ms
after: bloomfilter size:524288, about 2000W item cost about 400ms
1. support in/bloomfilter/minmax
2. support broadcast/shuffle/bucket shuffle/colocate join
3. opt memory use and cpu cache miss while build runtime filter
4. opt memory use in left semi join (works well on tpcds-95)
To avoid showing too many memtracker on BE web pages.
The MemTracker level now has 3 levels: OVERVIEW, TASK and VERBOSE.
OVERVIEW Mainly used for main memory consumption module such as Query/Load/Metadata.
TASK is mainly used to record the memory overhead of a single task such as a single query, load, and compaction task.
VERBOSE is used for other more detailed memtrackers.
`Select outfile into` currently only supports to export data with CSV format.
This patch extends the feature to supports parquet format.
Usage:
LocaFile:
```
SELECT citycode FROM table1 INTO OUTFILE "file:///root/doris/" FORMAT AS PARQUET PROPERTIES
("schema"="required,int32,siteid;", "parquet.compression"="snappy");
```
BrokerFile:
```
SELECT siteid FROM table1 INTO OUTFILE "hdfs://host/test_sql_prc_2019_02_19/" FORMAT AS PARQUET
PROPERTIES (
"broker.name" = "hdfs_broker",
"broker.hadoop.security.authentication" = "kerberos",
"broker.kerberos_principal" = "test",
"broker.kerberos_keytab_content" = "base64" ,
"schema"="required,int32,siteid;"
);
```
Field `schema` is required, which defines the schema of a parquet file.
Prefix `parquet.` is the parquet file properties, like compression, version, enable_dictionary.
For PR #5792. This patch add a new param `cache type` to distinguish sql cache and partition cache.
When update sql cache, we make assure one sql key only has one version cache.
If query is memory exceed, a detail info where memory exceed is required.
However it is not necessary to return the entire query stack to the end user.
The query stack only needs to be printed in the be log.
Support when creating a kafka routine load, start consumption from a specified point in time instead of a specific offset.
eg:
```
FROM KAFKA
(
"kafka_broker_list" = "broker1:9092,broker2:9092",
"kafka_topic" = "my_topic",
"property.kafka_default_offsets" = "2021-10-10 11:00:00"
);
or
FROM KAFKA
(
"kafka_broker_list" = "broker1:9092,broker2:9092",
"kafka_topic" = "my_topic",
"kafka_partitions" = "0,1,2",
"kafka_offsets" = "2021-10-10 11:00:00, 2021-10-10 11:00:00, 2021-10-10 12:00:00"
);
```
This PR also reconstructed the analysis method of properties when creating or altering
routine load jobs, and unified the analysis process in the `RoutineLoadDataSourceProperties` class.
1 Make some MemTracker have reasonable parent MemTracker not the root tracker
2 Make each MemTracker can be easily to trace.
3 Add show level of MemTracker to reduce the MemTracker show in the web page to have a way to control show how many tracker in web page.
* [Bug] Fix bug that database not found when replaying batch transaction remove log
[GlobalTransactionMgr.replayBatchRemoveTransactions():353] replay batch remove transactions failed. db 0
org.apache.doris.common.AnalysisException: errCode = 2, detailMessage = databaseTransactionMgr[0] does not exist
at org.apache.doris.transaction.GlobalTransactionMgr.getDatabaseTransactionMgr(GlobalTransactionMgr.java:84) ~[palo-fe.jar:3.4.0]
at org.apache.doris.transaction.GlobalTransactionMgr.replayBatchRemoveTransactions(GlobalTransactionMgr.java:350) [palo-fe.jar:3.4.0]
at org.apache.doris.persist.EditLog.loadJournal(EditLog.java:601) [palo-fe.jar:3.4.0]
at org.apache.doris.catalog.Catalog.replayJournal(Catalog.java:2452) [palo-fe.jar:3.4.0]
at org.apache.doris.master.Checkpoint.runAfterCatalogReady(Checkpoint.java:101) [palo-fe.jar:3.4.0]
at org.apache.doris.common.util.MasterDaemon.runOneCycle(MasterDaemon.java:58) [palo-fe.jar:3.4.0]
at org.apache.doris.common.util.Daemon.run(Daemon.java:116) [palo-fe.jar:3.4.0]
The id of information_scheam database is 0, and it has no txn at all.
1. Reduce lock conflicts in RuntimeProfile of be;
2. can view query profile when the query is executing;
3. reduce wait time for 'show proc /current_queries'.
This CL mainly changes:
1. Add a config to control the expire time of load job
Add a new FE config "streaming_label_keep_max_second" to control
the expire time of some high frequency load job such as INSERT and STREAM LOAD.
2. Remove expired txn in batch to avoid holding transaction lock for a long time
Record finished stream load job (both successful job and failed job) into audit log
so that we can see when the stream load job was executed and check the details of stream load jobs.
MemTracker can provide memory consumption for us to find out which
module consume more memory, but it's just a current value, this patch
add metrics for some large memory consumers, then we can find out
which module consume more memory in timeline, it would be useful to
troubleshoot OOM problems and optimize configs.
