Also fix BE ut:
1. fix scheme_change_test memory leak
2. fix mem_pool_test
Do not using DEFAULT_PADDING_SIZE = 0x10 in mem_pool when running ut.
3. remove plugin_test
* make ASAN poisoning work as much as possible
Before this patch a use after poison is reported like below
==19305==ERROR: AddressSanitizer: unknown-crash on address
0x625000137013 at pc 0x561c44bcf6b8 bp 0x7ffb75a00910 sp 0x7ffb75a000b8
After this patch the use after poison is reported like below
==17782==ERROR: AddressSanitizer: use-after-poison on address
0x625000137033 at pc 0x55633c8f56b8 bp 0x7ff3dc437930 sp 0x7ff3dc43
Before this patch, a false memory usage is reported like below
==33080==AddressSanitizer CHECK failed: ../../../../src/libsanitizer/
asan/asan_allocator.cpp:189 "((old)) == ((kAllocBegMagic))"
Support thread pool per disk for scanners to prevent pool performance from some high ioutil disks happening
key point:
1. each disk has a thread pool for scanners
2. whenever a thread pool of one disk runs out of local work, tasks can be retrieved from other threads(disks). This is done round-robin.
performance testing:
vec version: 25% faster than single thread pool in a high io util disk test case
normal version: 8% faster than single thread pool in a high io util disk test case
1. Fix the problem of BE crash caused by destruct sequence. (close#8058)
2. Add a new BE config `compaction_task_num_per_fast_disk`
This config specify the max concurrent compaction task num on fast disk(typically .SSD).
So that for high speed disk, we can execute more compaction task at same time,
to compact the data as soon as possible
3. Avoid frequent selection of unqualified tablet to perform compaction.
4. Modify some log level to reduce the log size of BE.
5. Modify some clone logic to handle error correctly.
The two phase batch commit means：
During Stream load, after data is written, the message will be returned to the client,
the data is invisible at this point and the transaction status is PRECOMMITTED.
The data will be visible only after COMMIT is triggered by client.
1. User can invoke the following interface to trigger commit operations for transaction：
curl -X PUT --location-trusted -u user:passwd -H "txn_id:txnId" -H "txn_operation:commit" \
http://fe_host:http_port/api/{db}/_stream_load_2pc
or
curl -X PUT --location-trusted -u user:passwd -H "txn_id:txnId" -H "txn_operation:commit" \
http://be_host:webserver_port/api/{db}/_stream_load_2pc
2.User can invoke the following interface to trigger abort operations for transaction：
curl -X PUT --location-trusted -u user:passwd -H "txn_id:txnId" -H "txn_operation:abort" \
http://fe_host:http_port/api/{db}/_stream_load_2pc
or
curl -X PUT --location-trusted -u user:passwd -H "txn_id:txnId" -H "txn_operation:abort" \
http://be_host:webserver_port/api/{db}/_stream_load_2pc
1. set both `tuple_offsets` and `new_tuple_offsets` in PRowBatch for compatibility
2. set FE config `repair_slow_replica` default to false
Avoid impacting the load process after upgrading.
Eg, if there are only 2 replicas, one is with high version count. After upgrade,
that replica will be set to bad, so that the load process will be stopped
because only 1 replica is alive.
3. Fix a bug that NodeChannel may be blocked at `close_wait()`
Forget to set `add_batch_finish` flag after the last rpc finished.
4. Fix a NPE of RoutineLoadScheduler
Support implement UDF through GRPC protocol. This brings several benefits:
1. The udf implementation language is not limited to c++, users can use any familiar language to implement udf
2. UDF is decoupled from Doris, udf will not cause doris coredump, udf computing resources are separated from doris, and doris services are not affected
But RPC's UDF has a fixed overhead, so its performance is much slower than C++ UDF, especially when the amount of data is large.
Create function like
```
CREATE FUNCTION rpc_add(INT, INT) RETURNS INT PROPERTIES (
"SYMBOL"="add_int",
"OBJECT_FILE"="127.0.0.1:9999",
"TYPE"="RPC"
);
```
Function service need to implement `check_fn` and `fn_call` methods
Note:
THIS IS AN EXPERIMENTAL FEATURE, THE INTERFACE AND DATA STRUCTURE MAY BE CHANGED IN FUTURE !!!
This PR mainly changes:
1. Fix bug when enable `transfer_data_by_brpc_attachment`
In `data_stream_sender`, we will send a serialized PRowBatch data to multiple Channels.
And if `transfer_data_by_brpc_attachment` is enabled, we will mistakenly clear the data in PRowBatch
after sending PRowBatch to the first Channel.
As a result, the following Channel cannot receive the correct data, causing an error.
So I use a separate buffer instead of `tuple_data` in PRowBatch to store the serialized data
and reuse it in multiple channels.
2. Fix bug that the the offset in serialized row batch may overflow
Use int64 to replace int32 offset. And for compatibility, add a new field `new_tuple_offsets` in PRowBatch.
The tuple ids of the empty set node must be exactly the same as the tuple ids of the origin root node.
In the issue, we found that once the tree where the root node is located has a window function,
the tuple ids of the empty set node cannot be calculated correctly.
This pr mostly fixes the problem.
In order to calculate the correct tuple ids,
the tuple ids obtained from the SelectStmt.getMaterializedTupleIds() function in the past
are changed to directly use the tuple ids of the origin root node.
Although we tried to fix#7929 by modifying the SelectStmt.getMaterializedTupleIds() function,
this method can't get the tuple of the last correct window function.
So we use other ways to construct tupleids of empty nodes.
Currently, if we encounter a problem with a replica of a tablet during the load process,
such as a write error, rpc error, -235, etc., it will cause the entire load job to fail,
which results in a significant reduction in Doris' fault tolerance.
This PR mainly changes:
1. refined the judgment of failed replicas in the load process, so that the failure of a few replicas will not affect the normal completion of the load job.
2. fix a bug introduced from #7754 that may cause BE coredump
This PR mainly changes:
1. Help to Cancel the load job ASAP when encounter unqualified data.
Solution is described in #6318 .
Also replace some std::stringstream with fmt::memory_buffer to avoid performance issues.
2. fix a NPE bug when create user with empty host
3. fix compile warning after rebasing the master(vectorization)
# Proposed changes
Issue Number: close#6238
Co-authored-by: HappenLee <happenlee@hotmail.com>
Co-authored-by: stdpain <34912776+stdpain@users.noreply.github.com>
Co-authored-by: Zhengguo Yang <yangzhgg@gmail.com>
Co-authored-by: wangbo <506340561@qq.com>
Co-authored-by: emmymiao87 <522274284@qq.com>
Co-authored-by: Pxl <952130278@qq.com>
Co-authored-by: zhangstar333 <87313068+zhangstar333@users.noreply.github.com>
Co-authored-by: thinker <zchw100@qq.com>
Co-authored-by: Zeno Yang <1521564989@qq.com>
Co-authored-by: Wang Shuo <wangshuo128@gmail.com>
Co-authored-by: zhoubintao <35688959+zbtzbtzbt@users.noreply.github.com>
Co-authored-by: Gabriel <gabrielleebuaa@gmail.com>
Co-authored-by: xinghuayu007 <1450306854@qq.com>
Co-authored-by: weizuo93 <weizuo@apache.org>
Co-authored-by: yiguolei <guoleiyi@tencent.com>
Co-authored-by: anneji-dev <85534151+anneji-dev@users.noreply.github.com>
Co-authored-by: awakeljw <993007281@qq.com>
Co-authored-by: taberylyang <95272637+taberylyang@users.noreply.github.com>
Co-authored-by: Cui Kaifeng <48012748+azurenake@users.noreply.github.com>
## Problem Summary:
### 1. Some code from clickhouse
**ClickHouse is an excellent implementation of the vectorized execution engine database,
so here we have referenced and learned a lot from its excellent implementation in terms of
data structure and function implementation.
We are based on ClickHouse v19.16.2.2 and would like to thank the ClickHouse community and developers.**
The following comment has been added to the code from Clickhouse, eg:
// This file is copied from
// https://github.com/ClickHouse/ClickHouse/blob/master/src/Interpreters/AggregationCommon.h
// and modified by Doris
### 2. Support exec node and query:
* vaggregation_node
* vanalytic_eval_node
* vassert_num_rows_node
* vblocking_join_node
* vcross_join_node
* vempty_set_node
* ves_http_scan_node
* vexcept_node
* vexchange_node
* vintersect_node
* vmysql_scan_node
* vodbc_scan_node
* volap_scan_node
* vrepeat_node
* vschema_scan_node
* vselect_node
* vset_operation_node
* vsort_node
* vunion_node
* vhash_join_node
You can run exec engine of SSB/TPCH and 70% TPCDS stand query test set.
### 3. Data Model
Vec Exec Engine Support **Dup/Agg/Unq** table, Support Block Reader Vectorized.
Segment Vec is working in process.
### 4. How to use
1. Set the environment variable `set enable_vectorized_engine = true; `(required)
2. Set the environment variable `set batch_size = 4096; ` (recommended)
### 5. Some diff from origin exec engine
https://github.com/doris-vectorized/doris-vectorized/issues/294
## Checklist(Required)
1. Does it affect the original behavior: (No)
2. Has unit tests been added: (Yes)
3. Has document been added or modified: (No)
4. Does it need to update dependencies: (No)
5. Are there any changes that cannot be rolled back: (Yes)
If an load task has a relatively short timeout, then we need to ensure that
each RPC of this task does not get blocked for a long time.
And an RPC is usually blocked for two reasons.
1. handling "memory exceeds limit" in the RPC
If the system finds that the memory occupied by the load exceeds the threshold,
it will select the load channel that occupies the most memory and flush the memtable in it.
this operation is done in the RPC, which may be more time consuming.
2. close the load channel
When the load channel receives the last batch, it will end the task.
It will wait for all memtables flushes to finish synchronously. This process is also time consuming.
Therefore, this PR solves this problem by.
1. Use timeout to determine whether it is a high-priority load task
If the timeout of an load task is relatively short, then we mark it as a high-priority task.
2. not processing "memory exceeds limit" for high priority tasks
3. use a separate flush thread to flush memtable for high priority tasks.
Support merge IN predicate when exist remote target(e.g. shuffle hash join).
Remote the code that IN predicate implicit conversion to Bloom filter then exist remote target.
Close related #7546
If the load result set is empty, or the load data is all filtered by the `where` condition,
it will not return failed with msg `all partitions have no load data`, but will return success directly.
For the first, we need to make a parameter to discribe the data is local or remote.
At then, we need to support some basic function to support the operation for remote storage.
