Now column `Array<T>` contains column `offsets` and `data`, and type of column `offsets` is UInt32 now.
If we call array_union to merge arrays repeatedly, the size of array may overflow.
So we need to extend it before `Array Data Type` release.
add some logic to opt compaction:
1.seperate base&cumu compaction in case base compaction runs too long and
affect cumu compaction
2.fix level size in cu compaction so that file size below 64M have a right level
size, when choose rowsets to do compaction, the policy will ignore big rowset,
this will reduce about 25% cpu in high frequency concurrent load
3.remove skip window restriction so rowset can do compaction right after
generated, cause we'll not delete rowset after compaction. This will highly
reduce compaction score in concurrent log.
4.remove version consistence check in can_do_compaction, we'll choose a
consecutive rowset to do compaction, so this logic is useless
after add logic above, compaction score and cpu cost will have a substantial
optimize in concurrent load.
Co-authored-by: yixiutt <yixiu@selectdb.com>
* [Vectorized][Function] add orthogonal bitmap agg functions
save some file about orthogonal bitmap function
add some file to rebase
update functions file
* refactor union_count function
refactor orthogonal union count functions
* remove bool is_variadic
In some cases, query mem tracker does not exist in BE when transmit block. This will result in a null pointer for get query mem tracker in brpc transmit_block
* compaction quickly for small data import #9791
1.merge small versions of rowset as soon as possible to increase the import frequency of small version data
2.small version means that the number of rows is less than config::small_compaction_rowset_rows default 1000
1. Provide a FE conf to test the reliability in single replica case when tablet scheduling are frequent.
2. According to #6063, almost apply this fix on current code.
1. Fix the memory leak. When the load task is canceled, the `IndexChannel` and `NodeChannel` mem trackers cannot be destructed in time.
2. Fix Load task being frequently canceled by oom and inaccurate `LoadChannel` mem tracker limit, and rewrite the variable name of `mem limit` in `LoadChannel`.
3. Fix core dump, when logout task mem tracker, phmap erase fails, resulting in repeated logout of the same tracker.
4. Fix the deadlock, when add_child_tracker mem limit exceeds, calling log_usage causes `_child_trackers_lock` deadlock.
5. Fix frequent log printing when thread mem tracker limit exceeds, which will affect readability and performance.
6. Optimize some details of mem tracker display.
At present, Doris can only access the hadoop cluster with kerberos authentication enabled by broker, but Doris BE itself
does not supports access to a kerberos-authenticated HDFS file.
This PR hope solve the problem.
When create hive external table, users just specify following properties to access the hdfs data with kerberos authentication enabled:
```sql
CREATE EXTERNAL TABLE t_hive (
k1 int NOT NULL COMMENT "",
k2 char(10) NOT NULL COMMENT "",
k3 datetime NOT NULL COMMENT "",
k5 varchar(20) NOT NULL COMMENT "",
k6 double NOT NULL COMMENT ""
) ENGINE=HIVE
COMMENT "HIVE"
PROPERTIES (
'hive.metastore.uris' = 'thrift://192.168.0.1:9083',
'database' = 'hive_db',
'table' = 'hive_table',
'dfs.nameservices'='hacluster',
'dfs.ha.namenodes.hacluster'='n1,n2',
'dfs.namenode.rpc-address.hacluster.n1'='192.168.0.1:8020',
'dfs.namenode.rpc-address.hacluster.n2'='192.168.0.2:8020',
'dfs.client.failover.proxy.provider.hacluster'='org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider',
'dfs.namenode.kerberos.principal'='hadoop/_HOST@REALM.COM'
'hadoop.security.authentication'='kerberos',
'hadoop.kerberos.principal'='doris_test@REALM.COM',
'hadoop.kerberos.keytab'='/path/to/doris_test.keytab'
);
```
If you want to `select into outfile` to HDFS that kerberos authentication enable, you can refer to the following SQL statement：
```sql
select * from test into outfile "hdfs://tmp/outfile1"
format as csv
properties
(
'fs.defaultFS'='hdfs://hacluster/',
'dfs.nameservices'='hacluster',
'dfs.ha.namenodes.hacluster'='n1,n2',
'dfs.namenode.rpc-address.hacluster.n1'='192.168.0.1:8020',
'dfs.namenode.rpc-address.hacluster.n2'='192.168.0.2:8020',
'dfs.client.failover.proxy.provider.hacluster'='org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider',
'dfs.namenode.kerberos.principal'='hadoop/_HOST@REALM.COM'
'hadoop.security.authentication'='kerberos',
'hadoop.kerberos.principal'='doris_test@REALM.COM',
'hadoop.kerberos.keytab'='/path/to/doris_test.keytab'
);
```
When the length of `Tuple/Block data` is greater than 2G, serialize the protoBuf request and embed the
`Tuple/Block data` into the controller attachment and transmit it through http brpc.
This is to avoid errors when the length of the protoBuf request exceeds 2G:
`Bad request, error_text=[E1003]Fail to compress request`.
In #7164, `Tuple/Block data` was put into attachment and sent via default `baidu_std brpc`,
but when the attachment exceeds 2G, it will be truncated. There is no 2G limit for sending via `http brpc`.
Also, in #7921, consider putting `Tuple/Block data` into attachment transport by default, as this theoretically
reduces one serialization and improves performance. However, the test found that the performance did not improve,
but the memory peak increased due to the addition of a memory copy.
1. add some metrics for cpu monitor;
2. add metrics for process state monitor;
3. add metrics for memory monitor;
It is convenient for us to use grafana to filter through different conditions.
After the added, we can find the cpu metrics like this：
doris_be_cpu{device="cpu1",mode="guest_nice"} 0
doris_be_cpu{device="cpu1",mode="guest"} 0
doris_be_cpu{device="cpu1",mode="steal"} 0
doris_be_cpu{device="cpu1",mode="soft_irq"} 107168
doris_be_cpu{device="cpu1",mode="irq"} 0
doris_be_cpu{device="cpu1",mode="iowait"} 3726931
doris_be_cpu{device="cpu1",mode="idle"} 2358039214
doris_be_cpu{device="cpu1",mode="system"} 58699464
doris_be_cpu{device="cpu1",mode="nice"} 1700438
doris_be_cpu{device="cpu1",mode="user"} 54974091
we can find the memory metrics as follow：
doris_be_memory_pswpin 167785
doris_be_memory_pswpout 203724
doris_be_memory_pgpgin 22308762092
doris_be_memory_pgpgout 152101956232
we also can find the process metrics as follow:
doris_be_proc{mode="interrupt"} 421721020416
doris_be_proc{mode="ctxt_switch"} 2806640907317
doris_be_proc{mode="procs_running"} 8
doris_be_proc{mode="procs_blocked"} 3
Add ntile function.
For non-vectorized-engine, I just implemented like Impala, rewrite ntile to row_number and count.
But for vectorized-engine, I implemented WindowFunctionNTile.
