- StarRocks
- Introduction to StarRocks
- Quick Start
- Deployment
- Deployment overview
- Prepare
- Deploy
- Deploy classic StarRocks
- Deploy and use shared-data StarRocks
- Manage
- Table Design
- Data Loading
- Concepts
- Overview of data loading
- Load data from a local file system or a streaming data source using HTTP PUT
- Load data from HDFS or cloud storage
- Load data from Apache Kafka®
- Load data from Apache Sparkâ„¢
- Load data using INSERT
- Load data using Stream Load transaction interface
- Synchronize data from MySQL in real time
- Continuously load data from Apache Flink®
- Change data through loading
- Transform data at loading
- Data Unloading
- Query Data Lakes
- Query Acceleration
- Gather CBO statistics
- Synchronous materialized views
- Asynchronous materialized views
- Colocate Join
- Lateral Join
- Query Cache
- Index
- Computing the Number of Distinct Values
- Sorted streaming aggregate
- Administration
- Management
- Data recovery
- User Privilege and Authentication
- Performance Tuning
- Reference
- SQL Reference
- User Account Management
- Cluster Management
- ADD SQLBLACKLIST
- ADMIN CANCEL REPAIR TABLE
- ADMIN CHECK TABLET
- ADMIN REPAIR TABLE
- ADMIN SET CONFIG
- ADMIN SET REPLICA STATUS
- ADMIN SHOW CONFIG
- ADMIN SHOW REPLICA DISTRIBUTION
- ADMIN SHOW REPLICA STATUS
- ALTER RESOURCE GROUP
- ALTER SYSTEM
- CANCEL DECOMMISSION
- CREATE FILE
- CREATE RESOURCE GROUP
- DELETE SQLBLACKLIST
- DROP FILE
- DROP RESOURCE GROUP
- EXPLAIN
- INSTALL PLUGIN
- KILL
- SET
- SHOW BACKENDS
- SHOW BROKER
- SHOW COMPUTE NODES
- SHOW FILE
- SHOW FRONTENDS
- SHOW FULL COLUMNS
- SHOW INDEX
- SHOW PLUGINS
- SHOW PROC
- SHOW PROCESSLIST
- SHOW RESOURCE GROUP
- SHOW SQLBLACKLIST
- SHOW TABLE STATUS
- SHOW VARIABLES
- UNINSTALL PLUGIN
- DDL
- ALTER DATABASE
- ALTER MATERIALIZED VIEW
- ALTER TABLE
- ALTER VIEW
- ALTER RESOURCE
- ANALYZE TABLE
- BACKUP
- CANCEL ALTER TABLE
- CANCEL BACKUP
- CANCEL RESTORE
- CREATE ANALYZE
- CREATE DATABASE
- CREATE EXTERNAL CATALOG
- CREATE FUNCTION
- CREATE INDEX
- CREATE MATERIALIZED VIEW
- CREATE REPOSITORY
- CREATE RESOURCE
- CREATE TABLE
- CREATE TABLE AS SELECT
- CREATE TABLE LIKE
- CREATE VIEW
- DROP ANALYZE
- DROP CATALOG
- DROP DATABASE
- DROP FUNCTION
- DROP INDEX
- DROP MATERIALIZED VIEW
- DROP REPOSITORY
- DROP RESOURCE
- DROP STATS
- DROP TABLE
- DROP VIEW
- HLL
- KILL ANALYZE
- RECOVER
- REFRESH EXTERNAL TABLE
- RESTORE
- SHOW ANALYZE JOB
- SHOW ANALYZE STATUS
- SHOW FUNCTION
- SHOW META
- SHOW RESOURCES
- TRUNCATE TABLE
- USE
- DML
- ALTER LOAD
- ALTER ROUTINE LOAD
- BROKER LOAD
- CANCEL LOAD
- CANCEL EXPORT
- CANCEL REFRESH MATERIALIZED VIEW
- CREATE ROUTINE LOAD
- DELETE
- EXPORT
- GROUP BY
- INSERT
- PAUSE ROUTINE LOAD
- REFRESH MATERIALIZED VIEW
- RESUME ROUTINE LOAD
- SELECT
- SHOW ALTER TABLE
- SHOW ALTER MATERIALIZED VIEW
- SHOW BACKUP
- SHOW CATALOGS
- SHOW CREATE CATALOG
- SHOW CREATE DATABASE
- SHOW CREATE MATERIALIZED VIEW
- SHOW CREATE TABLE
- SHOW CREATE VIEW
- SHOW DATA
- SHOW DATABASES
- SHOW DELETE
- SHOW DYNAMIC PARTITION TABLES
- SHOW EXPORT
- SHOW LOAD
- SHOW MATERIALIZED VIEW
- SHOW PARTITIONS
- SHOW PROPERTY
- SHOW REPOSITORIES
- SHOW RESTORE
- SHOW ROUTINE LOAD
- SHOW ROUTINE LOAD TASK
- SHOW SNAPSHOT
- SHOW TABLES
- SHOW TABLET
- SHOW TRANSACTION
- SPARK LOAD
- STOP ROUTINE LOAD
- STREAM LOAD
- UPDATE
- Auxiliary Commands
- Data Types
- Keywords
- Function Reference
- Function list
- Java UDFs
- Window functions
- Lambda expression
- Aggregate Functions
- any_value
- approx_count_distinct
- array_agg
- avg
- bitmap
- bitmap_agg
- count
- corr
- covar_pop
- covar_samp
- group_concat
- grouping
- grouping_id
- group_concat
- hll_empty
- hll_hash
- hll_raw_agg
- hll_union
- hll_union_agg
- max
- max_by
- min
- multi_distinct_sum
- multi_distinct_count
- percentile_approx
- percentile_cont
- percentile_disc
- retention
- stddev
- stddev_samp
- sum
- variance, variance_pop, var_pop
- var_samp
- window_funnel
- Array Functions
- array_agg
- array_append
- array_avg
- array_concat
- array_contains
- array_contains_all
- array_cum_sum
- array_difference
- array_distinct
- array_filter
- array_intersect
- array_join
- array_length
- array_map
- array_max
- array_min
- array_position
- array_remove
- array_slice
- array_sort
- array_sortby
- array_sum
- arrays_overlap
- array_to_bitmap
- reverse
- unnest
- Bit Functions
- Bitmap Functions
- base64_to_bitmap
- bitmap_agg
- bitmap_and
- bitmap_andnot
- bitmap_contains
- bitmap_count
- bitmap_from_string
- bitmap_empty
- bitmap_has_any
- bitmap_hash
- bitmap_intersect
- bitmap_max
- bitmap_min
- bitmap_or
- bitmap_remove
- bitmap_to_array
- bitmap_to_base64
- bitmap_to_string
- bitmap_union
- bitmap_union_count
- bitmap_union_int
- bitmap_xor
- intersect_count
- sub_bitmap
- to_bitmap
- Conditional Functions
- Cryptographic Functions
- Date Functions
- add_months
- adddate
- convert_tz
- current_date
- current_time
- current_timestamp
- date
- date_add
- date_format
- date_slice
- date_sub, subdate
- date_trunc
- datediff
- day
- dayname
- dayofmonth
- dayofweek
- dayofyear
- days_add
- days_diff
- days_sub
- from_days
- from_unixtime
- hour
- hours_sub
- microseconds_sub
- minute
- minutes_add
- minutes_diff
- minutes_sub
- month
- monthname
- months_add
- months_diff
- now
- quarter
- second
- seconds_add
- seconds_diff
- seconds_sub
- str_to_date
- str2date
- time_slice
- time_to_sec
- timediff
- timestamp
- timestampadd
- timestampdiff
- to_date
- to_days
- unix_timestamp
- utc_timestamp
- week
- weekofyear
- weeks_add
- weeks_diff
- weeks_sub
- year
- years_add
- years_diff
- years_sub
- Geographic Functions
- JSON Functions
- Overview of JSON functions and operators
- JSON operators
- JSON constructor functions
- JSON query and processing functions
- Map Functions
- Math Functions
- String Functions
- Pattern Matching Functions
- Percentile Functions
- Scalar Functions
- Utility Functions
- cast function
- hash function
- System variables
- User-defined variables
- Error code
- System limits
- AWS IAM policies
- SQL Reference
- FAQ
- Benchmark
- Ecosystem Release Notes
- Developers
- Contribute to StarRocks
- Code Style Guides
- Use the debuginfo file for debugging
- Development Environment
- Trace Tools
Synchronize data from MySQL in real time
What do I do if a Flink job reports an error?
A Flink job reports the error Could not execute SQL statement. Reason:org.apache.flink.table.api.ValidationException: One or more required options are missing.
A possible reason is that the required configuration information is missing in multiple sets of rules, such as [table-rule.1]
and [table-rule.2]
, in the SMT configuration file config_prod.conf.
You can check whether each set of rules, such as [table-rule.1]
and [table-rule.2]
is configured with the required database, table, and Flink connector information.
How can I make Flink automatically restart failed tasks?
Flink automatically restarts failed tasks through the checkpointing mechanism and restart strategy.
For example, if you need to enable the checkpointing mechanism and use the default restart strategy, which is the fixed delay restart strategy, you can configure the following information in the configuration file flink-conf.yaml:
execution.checkpointing.interval: 300000
state.backend: filesystem
state.checkpoints.dir: file:///tmp/flink-checkpoints-directory
Parameter description:
NOTE
For more detailed parameter descriptions in Flink documentation, see Checkpointing.
execution.checkpointing.interval
: the base time interval of checkpointing. Unit: millisecond. To enable the checkpointing mechanism, you need to set this parameter to a value greater than0
.state.backend
: specifies the state backend to determine how the state is represented internally, and how and where it is persisted upon checkpointing. Common values arefilesystem
orrocksdb
. After the checkpointing mechanism is enabled, the state is persisted upon checkpoints to prevent data loss and ensure data consistency after recovery. For more information on state, see State Backends.state.checkpoints.dir
: the directory to which checkpoints are written to.
How can I manually stop a Flink job and later restore it to the state before stopping?
You can manually trigger a savepoint when stopping a Flink job (a savepoint is a consistent image of the execution state of a streaming Flink job, and is created based on the checkpointing mechanism). Later, you can restore the Flink job from the specified savepoint.
Stop the Flink job with a savepoint. The following command automatically triggers a savepoint for the Flink job
jobId
and stops the Flink job. Additionally, you can specify a target file system directory to store the savepoint.bin/flink stop --type [native/canonical] --savepointPath [:targetDirectory] :jobId
Parameter description:
jobId
: You can view the Flink job ID from the Flink WebUI or by runningflink list -running
on the command line.targetDirectory
: You can specifystate.savepoints.dir
as the default directory for storing savepoints in the Flink configuration file flink-conf.yml. When a savepoint is triggered, the savepoint is stored in this default directory and you do not need to specify a directory .
state.savepoints.dir: [file:// or hdfs://]/home/user/savepoints_dir
Resubmit the Flink job with the preceding savepoint specified.
./flink run -c com.starrocks.connector.flink.tools.ExecuteSQL -s savepoints_dir/savepoints-xxxxxxxx flink-connector-starrocks-xxxx.jar -f flink-create.all.sql