- 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
- Continuously load data from Apache Kafka®
- Bulk load using Apache Sparkâ„¢
- Load data using INSERT
- Load data using Stream Load transaction interface
- Realtime synchronization from MySQL
- Continuously load data from Apache Flink®
- Change data through loading
- Transform data at loading
- Data Unloading
- Query Data Sources
- Query Acceleration
- Gather CBO statistics
- Synchronous materialized view
- Asynchronous materialized view
- 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 INDEX
- CREATE MATERIALIZED VIEW
- CREATE REPOSITORY
- CREATE RESOURCE
- CREATE TABLE AS SELECT
- CREATE TABLE LIKE
- CREATE TABLE
- CREATE VIEW
- CREATE FUNCTION
- DROP ANALYZE
- DROP STATS
- DROP CATALOG
- DROP DATABASE
- DROP INDEX
- DROP MATERIALIZED VIEW
- DROP REPOSITORY
- DROP RESOURCE
- DROP TABLE
- DROP VIEW
- DROP FUNCTION
- HLL
- KILL ANALYZE
- RECOVER
- REFRESH EXTERNAL TABLE
- RESTORE
- SET CATALOG
- SHOW ANALYZE JOB
- SHOW ANALYZE STATUS
- SHOW META
- SHOW RESOURCES
- SHOW FUNCTION
- 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 MATERIALIZED VIEW
- SHOW CREATE TABLE
- SHOW CREATE VIEW
- SHOW DATA
- SHOW DATABASES
- SHOW DELETE
- SHOW DYNAMIC PARTITION TABLES
- SHOW EXPORT
- SHOW LOAD
- SHOW MATERIALIZED VIEWS
- 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
- SUBMIT TASK
- UPDATE
- Auxiliary Commands
- Data Types
- Keywords
- AUTO_INCREMENT
- Function Reference
- Java UDFs
- Window functions
- Lambda expression
- Aggregate Functions
- array_agg
- avg
- any_value
- approx_count_distinct
- bitmap
- bitmap_agg
- count
- grouping
- grouping_id
- 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
- cardinality
- element_at
- 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
- JSON Functions
- Overview of JSON functions and operators
- JSON operators
- JSON constructor functions
- JSON query and processing functions
- Map Functions
- Binary Functions
- 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_add
- hours_diff
- hours_sub
- microseconds_add
- microseconds_sub
- minute
- minutes_add
- minutes_diff
- minutes_sub
- month
- monthname
- months_add
- months_diff
- months_sub
- 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
- week_iso
- weekofyear
- weeks_add
- weeks_diff
- weeks_sub
- year
- years_add
- years_diff
- years_sub
- Geographic Functions
- Math Functions
- String Functions
- append_trailing_char_if_absent
- ascii
- char
- char_length
- character_length
- concat
- concat_ws
- ends_with
- find_in_set
- group_concat
- hex
- hex_decode_binary
- hex_decode_string
- instr
- lcase
- left
- length
- locate
- lower
- lpad
- ltrim
- money_format
- null_or_empty
- parse_url
- repeat
- replace
- reverse
- right
- rpad
- rtrim
- space
- split
- split_part
- starts_with
- strleft
- strright
- substring
- trim
- ucase
- unhex
- upper
- Pattern Matching Functions
- Percentile Functions
- Scalar Functions
- Utility Functions
- cast function
- hash function
- System variables
- User-defined variables
- Error code
- System limits
- SQL Reference
- FAQ
- Benchmark
- Developers
- Contribute to StarRocks
- Code Style Guides
- Use the debuginfo file for debugging
- Development Environment
- Trace Tools
- Integration
Duplicate Key table
The Duplicate Key table is the default model in StarRocks. If you did not specify a model when you create a table, a Duplicate Key table is created by default.
When you create a Duplicate Key table, you can define a sort key for that table. If the filter conditions contain the sort key columns, StarRocks can quickly filter data from the table to accelerate queries. The Duplicate Key table allows you to append new data to the table. However, it does not allow you to modify existing data in the table.
Scenarios
The Duplicate Key table is suitable for the following scenarios:
- Analyze raw data, such as raw logs and raw operation records.
- Query data by using a variety of methods without being limited by the pre-aggregation method.
- Load log data or time-series data. New data is written in append-only mode, and existing data is not updated.
Create a table
Suppose that you want to analyze the event data over a specific time range. In this example, create a table named detail
and define event_time
and event_type
as sort key columns.
Statement for creating the table:
CREATE TABLE IF NOT EXISTS detail (
event_time DATETIME NOT NULL COMMENT "datetime of event",
event_type INT NOT NULL COMMENT "type of event",
user_id INT COMMENT "id of user",
device_code INT COMMENT "device code",
channel INT COMMENT ""
)
DUPLICATE KEY(event_time, event_type)
DISTRIBUTED BY HASH(user_id) BUCKETS 8;
You must specify
DISTRIBUTED BY HASH
. Otherwise, the table creation fails.
Usage notes
Take note of the following points about the sort key of a table:
You can use the
DUPLICATE KEY
keyword to explicitly define the columns that are used in the sort key.Note: By default, if you do not specify sort key columns, StarRocks uses the first three columns as sort key columns.
In the Duplicate Key table, the sort key can consist of some or all of the dimension columns.
You can create indexes such as BITMAP indexes and Bloomfilter indexes at table creation.
If two identical records are loaded, the Duplicate Key table retains them as two records, rather than one.
What to do next
After a table is created, you can use various data ingestion methods to load data into StarRocks. For information about the data ingestion methods that are supported by StarRocks, see Overview of data loading.
Note: When you load data into a table that uses the Duplicate Key table, you can only append data to the table. You cannot modify the existing data in the table.