Record query consumption into fe audit log. Its basic mode of work is as follows, one of instance of parent plan is responsible for accumulating sub plan's consumption and send to it's parent, BE coordinator will get total consumption because it's a single instance.
Help to locate big query when system overload, by checking consumptions of running parts of current all queries or specified one query. Its basic mode of work is as follows: firstly trigger BE to report RuntimeProfiles, and wait a moment. secondly caculate consumptions with RuntimeProfiles reported by BE. The consumptions supported by it are the cost of running ExecNode in query when call it.
1. Add sql parser and sql scanner for routine load stmt such as KW_ROUTINE(routine), KW_PAUSE.
2. Create routine load statment like
CREATE ROUTINE LOAD name ON database.table
(properties of routine load)
[PROPERTIES (key1=value1, )]
FROM [KAFKA](type of routine load)
(properties of this type)
properties of routine load:
The load property of CreateRoutineLoadStmt is disordered: Both 'LoadColumnsInfo, PartitionNames xxx' and 'PartitionNames, ColumnsInfo xxx' is right.
[COLUMNS TERMINATED BY separator ]
[(col1, ...)]
[SET (k1=f1(xx), k2=f2(xx))]
WHERE
[PARTITION (p1, p2)]
type of routine load:
KAFKA
different type has different properties
properties of this type:
k1 = v1
k2 = v2
3. Pause/Resume/Stop routine load statment like
PAUSE/RESUME/STOP ROUTINE LOAD jobName
4. Ddlexecutor support CreateRoutineLoadStmt, Pause/Resume/StopRoutineLoadStmt
5. Pause/Stop routine load will clear all of task which belong to job immediately
The task which has been not committed will be abort.
6. Resume routine load will change job state to need scheduler
The RoutineLoadJobScheduler will scheduler it later.
7. Show routine load statment like
SHOW ROUTINE LOAD jobName
8. All of load property can implement LoadProperty such as LoadColumnsInfo, PartitionsNames etc
9. The sql of LoadColumnsInfo is Columns (c1, c2, c3) set (c1, c2, c3=c1+c2)
10. Add check of routineLoadName, db.routineLoadName is unique in database when job state is not final state.
1. Add broker load error hub
A broker load error hub will collect error messages in load process and saves them as a file to the specified remote storage via broker. In case that in broker/min/streaming load process, user may not be able to access the error log file in Backend directly.
We also add a new header option: 'enable_hub' in streaming load request, and default is false. Because if we enable the broker load error hub, it will significantly slow down the processing speed of streaming load, due to the visit of remote storage via broker. So use can disable the error load hub using this header option, to avoid slowing down the load speed.
2. Show load error logs by using SHOW LOAD WARNINGS stmt
We also provide a more easy way to get load error logs. We implement 'SHOW LOAD WARNINGS ON 'url'' stmt to show load error logs directly. The 'url' in stmt is provided in 'SHOW LOAD' stmt.
eg:
show load warnings on "http://192.168.1.1:8040/api/_load_error_log?file=__shard_2/error_log_xxx";
3. Support now() function in broker load
User can mapping a column to now() in broker load stmt, which means this column will be filled with time when the ETL started.
4. Support more types of wildcard in broker load
Currently, we only support wildcard '*' to match the file names. wildcard like '/path/to/20190[1-4]*' is not support.
In TabletInvertedIndex calss, The instance of TabletMeta in
'tabletMetaMap' and 'tabletMetaTable' should be same.
Otherwise when we change the schema hash info of TabletMeta
in 'tabletMetaMap', TabletMeta in 'tabletMetaTable' left
unchanged, which will cause inconsistency of meta.
1. Print broker address for debug.
2. Do not letting backup job cancelled if it already in state UPLOAD_INFO.
3. Cancel task on Backends when job is cancelled.
4. Show detail progress of backup and restore job.
5. Make 'show snapshot' result more readable.
6. Change upload and download thread num of backup and restore in Backend to 1.
Partition.updateVisibleVersionAndVersionHash() is the only method that
may call Catalog.getCurrentCatalogJournalVersion() in a non-replay thread.
So we have to check whether MetaContext is null. If MetaContext is null, which
means this is a non-replay thread, and we do not need call Catalog.getCurrentCatalogJournalVersion().
Also modify the load logic to make delete job done more quickly.
Because the meta version is only be used in catalog saving and loading.
So currently this version is a field of Catalog class. And we can get this
version only by calling Catalog.getCurrentCatalogJournalVersion().
But in restore process, we need to read the meta data which is saved with
a specified meta version. So we need a flexible way to read a meta data
using a specified meta version, not only the version from Catalog.
So we create a new class called MetaContext. Currently it only has one field,
'journalVersion', to save the current journal version. And it is a
thread local variable, so that we can create a MetaContext anywhere we want,
and setting the 'journalVersion' which we want to use for reading meta.
Currently, there are 4 threads which is related to meta data saving and loading.
The Frontend starting thread, which will call Catalog.initialize() to load the image.
the Frontend state listener thread, which will listen the state changing, and call
transferToMaster() or transferToNonMaster().
Edit log replayed thread, which is created when calling transferToNonMaster().
It will replay edit log
Checkpoint thread, which is created when calling transferToMaster(). It will do
the checkpoint periodically.
Notice that we get the 'current meta version' only when 'READING' the meta (not WRITING).
So we only need to take care of all 'READING' threads.
We create MetaContext thread local variable for these 4 threads, and thread 2,3,4's
meta context inherit from thread 1's meta context. Because thread 1 will load the origin
image file and get the very first meta version.
And we leave the Catalog.getCurrentCatalogJournalVersion()'s name unchanged, just
change its content, because we don't want change a lot codes this time.
On the other hand, we add the current meta version in backup job info file when doing
backup job. So that when restoring from a backup snapshot, we can know which meta
version we should use for read the meta.
And also , we add a new property "meta_version" for Restore stmt, so that we can specify
the meta version used for reading backup meta. It is for those old backup snapshots
which do not has meta version saving in backup job info file.
1. add a needSchedulerTasksQueue in LoadManager: the RoutineLoadTaskScheduler will poll task from this queue and schedule task.
2. add a frontend interface named rlTaskCommit: commit txn, update offset and renew a task for the same partitions
3. add extra property in transaction state: in rlTaskCommit, extra property which looks like {"job_id": xxx, "progress": xxx}
When fe initialize routine load job meta from logs, all of txn state which related to routine load job will be used for initializing progress of job.
Add a TxnStateChangeListener interface for transaction
1. onCommitted , onAborted, beforeAborted will be called by different type of txn
2. RoutineLoadJob will update job progress and renew a task when onCommitted callback
3. Add TxnStateChangeListener into TransactionState
4. set transactionState to committed will call onCommitted callback if callback is not null
5. set transactionState to aborted will call beforeAborted and onAborted
6. beforeAborted in RoutineLoadJob will check if there is related task when TxnStatusChangeReason is TIMEOUT. It will prevent abort when there is a related task by throw TransactionException
7. Other reason of abort will not prevent abort. The onAborted will be call and job state will be change to paused
Change extra to TxnCommitAttachment in TLoadTxnCommitRequest
1. The KAFKA source of TTxnSourceType means that this is a routine load task commit. And the TRLTaskTxnCommitAttachment is the commitInfo of this task.
2. TRLTaskTxnCommitAttachment will be convert to RLTaskTxnCommitAttachment which include progress of this task, task id, numOfErrorData etc.
Add param TxnCommitAttachment into commitTransaction
1. The TxnCommitAttachment will be updated in commitTransaction
When heartbeat failed, we should clear the connections cached
in client pool, or we will get broken connections from the pool.
Since we don't have the REOPEN logic(which may cause ugly code style),
a broken connection may cause a rpc blocked and failed.
So clear them all and recreate them when needed is a simple way to
resolve this problem.
We only clear connections in backend and broker pool.
No need to clear heartbeat pool because heartbeat is very frequent,
such the connections can be invalid automatically.
* Refactor heartbeat logic
Currently we only have Backend heartbeat. And without Frontend
or Broker heartbeat, we don't know the status of these nodes,
thus can't do failover logic in some cases.
1. Add Frontend and Broker heartbeat.
Frontend heartbeat using BootstrapFinish http rest api
Broker heartbeat using ping() rpc.
2. All heartbeats are managed in HeartbeatMgr.
3. Rename BrokerAddress to FsBroker.
* Support colocate join
Colocate join means two table are distributed by the columns being joined,
then we can join them locally on each backend.
Colocate join no data movement and has more concurrency.
* Support TRUNCATE TABLE stmt
User can use TRUNCATE TABLE stmt to empties a table
or partitions completely.
Unlike DELETE, it will drop the tablets directly, and
without any performance impact.
* Fix bugs that new partition should use new ID
* Use equals() to compare Integer
* Fix compile bug
* Fix bug on single range parititon
* Check table's state again after creating partition
* Avoid 'No more data to read' error when handling stream load rpc
1. Catch throwable of all stream load rpc.
2. Avoid setting null string as error msg of rpc result status.
* Change setError_msgs to addToError_msgs
1. Only collect all error replicas if publish task is timeout.
2. Add 2 metrics to monitor the success of failure of txn.
3. Change publish timeout to Config.load_straggler_wait_second
Step1: updateBeIdTaskMaps, remove unavailable BE and add new alive BE
Step2: process timeout tasks, if a task has already been allocated to BE but not finished before DEFAULT_TASK_TIMEOUT, it will be discarded.
At the same time, the partitions belong to old tasks will be allocated to a new task. The new task with a signature will be added in the queue of needSchedulerRoutineLoadTask.
Step3: process all needSchedulerRoutineLoadTasks, allocate task to BE. The task will be executed by BE.
* Modify partition's version name to what it means.
1. committedVersion(Hash) -> visibleVersion(Hash)
2. currentVersion(Hash) -> committedVersion(Hash)
3. add some comment to make the code more readable
* Check if editlog is null in CatalogIdGenerator
To avoid unit test failure
* Change PaloMetrics' name and Catalog's Id generator
1. Remove 'Palo' prefix of class Metric.
2. Add a new CatalogIdGenerator to replace the old AtomicLong, to avoid too many edit logs.
3. Add a new histogram to monitor write letency of edit log write.
* modify next id logic
* fix a bug that Metric is not init before using HISTO_EDIT_LOG_WRITE_LATENCY
* fix a problem
Add path info of replica in catalog
Also fix a bug that when calling check_none_row_oriented_table,
store is null, it cannot be used to create table.
Instead, OLAPHeader can be used to get storage type information.
