4.5 KiB
title, language
| title | language |
|---|---|
| BITMAP | en |
BITMAP
Create table
The aggregation model needs to be used when creating the table. The data type is bitmap and the aggregation function is bitmap_union.
CREATE TABLE `pv_bitmap` (
`dt` int (11) NULL COMMENT" ",
`page` varchar (10) NULL COMMENT" ",
`user_id` bitmap BITMAP_UNION NULL COMMENT" "
) ENGINE = OLAP
AGGREGATE KEY (`dt`,` page`)
COMMENT "OLAP"
DISTRIBUTED BY HASH (`dt`) BUCKETS 2;
Note: When the amount of data is large, it is best to create a corresponding rollup table for high-frequency bitmap_union queries
ALTER TABLE pv_bitmap ADD ROLLUP pv (page, user_id);
Data Load
TO_BITMAP (expr): Convert 0 ~ 18446744073709551615 unsigned bigint to bitmap
BITMAP_EMPTY (): Generate empty bitmap columns, used for insert or import to fill the default value
BITMAP_HASH (expr): Convert any type of column to a bitmap by hashing
Stream Load
cat data | curl --location-trusted -u user: passwd -T--H "columns: dt, page, user_id, user_id = to_bitmap (user_id)" http: // host: 8410 / api / test / testDb / _stream_load
cat data | curl --location-trusted -u user: passwd -T--H "columns: dt, page, user_id, user_id = bitmap_hash (user_id)" http: // host: 8410 / api / test / testDb / _stream_load
cat data | curl --location-trusted -u user: passwd -T--H "columns: dt, page, user_id, user_id = bitmap_empty ()" http: // host: 8410 / api / test / testDb / _stream_load
Insert Into
id2's column type is bitmap
insert into bitmap_table1 select id, id2 from bitmap_table2;
id2's column type is bitmap
INSERT INTO bitmap_table1 (id, id2) VALUES (1001, to_bitmap (1000)), (1001, to_bitmap (2000));
id2's column type is bitmap
insert into bitmap_table1 select id, bitmap_union (id2) from bitmap_table2 group by id;
id2's column type is int
insert into bitmap_table1 select id, to_bitmap (id2) from table;
id2's column type is String
insert into bitmap_table1 select id, bitmap_hash (id_string) from table;
Data Query
Syntax
BITMAP_UNION (expr): Calculate the union of two Bitmaps. The return value is the new Bitmap value.
BITMAP_UNION_COUNT (expr): Calculate the cardinality of the union of two Bitmaps, equivalent to BITMAP_COUNT (BITMAP_UNION (expr)). It is recommended to use the BITMAP_UNION_COUNT function first, its performance is better than BITMAP_COUNT (BITMAP_UNION (expr)).
BITMAP_UNION_INT (expr): Count the number of different values in columns of type TINYINT, SMALLINT and INT, return the sum of COUNT (DISTINCT expr) same
INTERSECT_COUNT (bitmap_column_to_count, filter_column, filter_values ...): The calculation satisfies
filter_column The cardinality of the intersection of multiple bitmaps of the filter.
bitmap_column_to_count is a column of type bitmap, filter_column is a column of varying dimensions, and filter_values is a list of dimension values.
Example
The following SQL uses the pv_bitmap table above as an example:
Calculate the deduplication value for user_id:
select bitmap_union_count (user_id) from pv_bitmap;
select bitmap_count (bitmap_union (user_id)) from pv_bitmap;
Calculate the deduplication value of id:
select bitmap_union_int (id) from pv_bitmap;
Calculate the retention of user_id:
select intersect_count (user_id, page, 'meituan') as meituan_uv,
intersect_count (user_id, page, 'waimai') as waimai_uv,
intersect_count (user_id, page, 'meituan', 'waimai') as retention // Number of users appearing on both 'meituan' and 'waimai' pages
from pv_bitmap
where page in ('meituan', 'waimai');
keyword
BITMAP, BITMAP_COUNT, BITMAP_EMPTY, BITMAP_UNION, BITMAP_UNION_INT, TO_BITMAP, BITMAP_UNION_COUNT, INTERSECT_COUNT