创建表

0)启动Hive的Metastore

nohup hive --service metastore & 

1)启动spark-sql
#针对Spark 3.2

spark-sql \
  --conf 'spark.serializer=org.apache.spark.serializer.KryoSerializer' \
  --conf 'spark.sql.catalog.spark_catalog=org.apache.spark.sql.hudi.catalog.HoodieCatalog' \
  --conf 'spark.sql.extensions=org.apache.spark.sql.hudi.HoodieSparkSessionExtension'

如果没有配置hive环境变量,手动拷贝hive-site.xml到spark的conf下
2)建表参数

参数名默认值说明
primaryKeyuuid表的主键名,多个字段用逗号分隔,同 hoodie.datasource.write.recordkey.field
preCombineField表的预合并字段。同 hoodie.datasource.write.precombine.field
typecow创建的表类型:type = ‘cow’ , type = ‘mor’ ;同hoodie.datasource.write.table.type

3)创建非分区表
1.创建一个cow表,默认primaryKey ‘uuid’,不提供preCombineField

create table hudi_cow_nonpcf_tbl (
  uuid int,
  name string,
  price double
) using hudi;

2.创建一个mor非分区表

create table hudi_mor_tbl (
  id int,
  name string,
  price double,
  ts bigint
) using hudi
tblproperties (
  type = 'mor',
  primaryKey = 'id',
  preCombineField = 'ts'
);

4)创建分区表
创建一个cow分区外部表,指定primaryKey和preCombineField

create table hudi_cow_pt_tbl (
  id bigint,
  name string,
  ts bigint,
  dt string,
  hh string
) using hudi
tblproperties (
  type = 'cow',
  primaryKey = 'id',
  preCombineField = 'ts'
 )
partitioned by (dt, hh)
location '/tmp/hudi/hudi_cow_pt_tbl';

5)在已有的hudi表上创建新表
不需要指定模式和非分区列(如果存在)之外的任何属性,Hudi可以自动识别模式和配置。
1.非分区表

create table hudi_existing_tbl0 using hudi
location 'file:///tmp/hudi/dataframe_hudi_nonpt_table';

2.分区表

create table hudi_existing_tbl1 using hudi
partitioned by (dt, hh)
location 'file:///tmp/hudi/dataframe_hudi_pt_table';

6)通过CTAS (Create Table As Select)建表
为了提高向hudi表加载数据的性能,CTAS使用批量插入作为写操作。
1.通过CTAS创建cow非分区表,不指定preCombineField

create table hudi_ctas_cow_nonpcf_tbl
using hudi
tblproperties (primaryKey = 'id')
as
select 1 as id, 'a1' as name, 10 as price;

2.通过CTAS创建cow分区表,指定preCombineField

create table hudi_ctas_cow_pt_tbl
using hudi
tblproperties (type = 'cow', primaryKey = 'id', preCombineField = 'ts')
partitioned by (dt)
as
select 1 as id, 'a1' as name, 10 as price, 1000 as ts, '2021-12-01' as dt;

3.通过CTAS从其他表加载数据
创建内部表

create table parquet_mngd using parquet location 'file:///tmp/parquet_dataset/*.parquet';

通过CTAS加载数据

create table hudi_ctas_cow_pt_tbl2 using hudi location 'file:/tmp/hudi/hudi_tbl/' options (
  type = 'cow',
  primaryKey = 'id',
  preCombineField = 'ts'
 )
partitioned by (datestr) as select * from parquet_mngd;

插入数据

默认情况下,如果提供了preCombineKey,则insert into的写操作类型为upsert,否则使用insert。
1)向非分区表插入数据

insert into hudi_cow_nonpcf_tbl select 1, 'a1', 20;
insert into hudi_mor_tbl select 1, 'a1', 20, 1000;

2)向分区表动态分区插入数据

insert into hudi_cow_pt_tbl partition (dt, hh)
select 1 as id, 'a1' as name, 1000 as ts, '2021-12-09' as dt, '10' as hh;

3)向分区表静态分区插入数据

insert into hudi_cow_pt_tbl partition(dt = '2021-12-09', hh='11') select 2, 'a2', 1000;

4)使用bulk_insert插入数据
hudi支持使用bulk_insert作为写操作的类型,只需要设置两个配置:
hoodie.sql.bulk.insert.enable和hoodie.sql.insert.mode。

-- 向指定preCombineKey的表插入数据,则写操作为upsert
insert into hudi_mor_tbl select 1, 'a1_1', 20, 1001;
select id, name, price, ts from hudi_mor_tbl;
1   a1_1    20.0    1001
-- 向指定preCombineKey的表插入数据,指定写操作为bulk_insert 
set hoodie.sql.bulk.insert.enable=true;
set hoodie.sql.insert.mode=non-strict;

insert into hudi_mor_tbl select 1, 'a1_2', 20, 1002;
select id, name, price, ts from hudi_mor_tbl;
1   a1_1    20.0    1001
1   a1_2    20.0    1002

查询数据

1)查询

select fare, begin_lon, begin_lat, ts from  hudi_trips_snapshot where fare > 20.0

2)时间旅行查询
Hudi从0.9.0开始就支持时间旅行查询。Spark SQL方式要求Spark版本 3.2及以上。
– 关闭前面开启的bulk_insert

set hoodie.sql.bulk.insert.enable=false;

create table hudi_cow_pt_tbl1 (
  id bigint,
  name string,
  ts bigint,
  dt string,
  hh string
) using hudi
tblproperties (
  type = 'cow',
  primaryKey = 'id',
  preCombineField = 'ts'
 )
partitioned by (dt, hh)
location '/tmp/hudi/hudi_cow_pt_tbl1';

– 插入一条id为1的数据

insert into hudi_cow_pt_tbl1 select 1, 'a0', 1000, '2021-12-09', '10';
select * from hudi_cow_pt_tbl1;

– 修改id为1的数据

insert into hudi_cow_pt_tbl1 select 1, 'a1', 1001, '2021-12-09', '10';
select * from hudi_cow_pt_tbl1;

– 基于第一次提交时间进行时间旅行

select * from hudi_cow_pt_tbl1 timestamp as of '20220307091628793' where id = 1;

– 其他时间格式的时间旅行写法

select * from hudi_cow_pt_tbl1 timestamp as of '2022-03-07 09:16:28.100' where id = 1;

select * from hudi_cow_pt_tbl1 timestamp as of '2022-03-08' where id = 1;

更新数据

1)update
更新操作需要指定preCombineField。
(1)语法

UPDATE tableIdentifier SET column = EXPRESSION(,column = EXPRESSION) [ WHERE boolExpression]

(2)执行更新

update hudi_mor_tbl set price = price * 2, ts = 1111 where id = 1;

update hudi_cow_pt_tbl1 set name = 'a1_1', ts = 1001 where id = 1;

– update using non-PK field

update hudi_cow_pt_tbl1 set ts = 1111 where name = 'a1_1';

2)MergeInto
(1)语法

MERGE INTO tableIdentifier AS target_alias
USING (sub_query | tableIdentifier) AS source_alias
ON <merge_condition>
[ WHEN MATCHED [ AND <condition> ] THEN <matched_action> ]
[ WHEN MATCHED [ AND <condition> ] THEN <matched_action> ]
[ WHEN NOT MATCHED [ AND <condition> ]  THEN <not_matched_action> ]
<merge_condition> =A equal bool condition 
<matched_action>  =
  DELETE  |
  UPDATE SET *  |
  UPDATE SET column1 = expression1 [, column2 = expression2 ...]
<not_matched_action>  =
  INSERT *  |
  INSERT (column1 [, column2 ...]) VALUES (value1 [, value2 ...])

(2)执行案例
– 1、准备source表:非分区的hudi表,插入数据

create table merge_source (id int, name string, price double, ts bigint) using hudi
tblproperties (primaryKey = 'id', preCombineField = 'ts');
insert into merge_source values (1, "old_a1", 22.22, 2900), (2, "new_a2", 33.33, 2000), (3, "new_a3", 44.44, 2000);

merge into hudi_mor_tbl as target
using merge_source as source
on target.id = source.id
when matched then update set *//给定一条数据,若数据库中有则更新该数据,没有则新增一条数据
when not matched then insert *

;

– 2、准备source表:分区的parquet表,插入数据

create table merge_source2 (id int, name string, flag string, dt string, hh string) using parquet;
insert into merge_source2 values (1, "new_a1", 'update', '2021-12-09', '10'), (2, "new_a2", 'delete', '2021-12-09', '11'), (3, "new_a3", 'insert', '2021-12-09', '12');

merge into hudi_cow_pt_tbl1 as target
using (
  select id, name, '2000' as ts, flag, dt, hh from merge_source2
) source
on target.id = source.id
when matched and flag != 'delete' then
 update set id = source.id, name = source.name, ts = source.ts, dt = source.dt, hh = source.hh
when matched and flag = 'delete' then delete
when not matched then
 insert (id, name, ts, dt, hh) values(source.id, source.name, source.ts, source.dt, source.hh)

删除数据

1)语法

DELETE FROM tableIdentifier [ WHERE BOOL_EXPRESSION]

2)案例

delete from hudi_cow_nonpcf_tbl where uuid = 1;

delete from hudi_mor_tbl where id % 2 = 0;

– 使用非主键字段删除

delete from hudi_cow_pt_tbl1 where name = 'a1_1';

覆盖数据

使用INSERT_OVERWRITE类型的写操作覆盖分区表
使用INSERT_OVERWRITE_TABLE类型的写操作插入覆盖非分区表或分区表(动态分区)
1)insert overwrite 非分区表

insert overwrite hudi_mor_tbl select 99, 'a99', 20.0, 900;
insert overwrite hudi_cow_nonpcf_tbl select 99, 'a99', 20.0;

2)通过动态分区insert overwrite table到分区表

insert overwrite table hudi_cow_pt_tbl1 select 10, 'a10', 1100, '2021-12-09', '11';

3)通过静态分区insert overwrite 分区表

insert overwrite hudi_cow_pt_tbl1 partition(dt = '2021-12-09', hh='12') select 13, 'a13', 1100;

修改表结构(Alter Table)

1)语法

-- Alter table name
ALTER TABLE oldTableName RENAME TO newTableName

-- Alter table add columns
ALTER TABLE tableIdentifier ADD COLUMNS(colAndType (,colAndType)*)

-- Alter table column type
ALTER TABLE tableIdentifier CHANGE COLUMN colName colName colType

-- Alter table properties
ALTER TABLE tableIdentifier SET TBLPROPERTIES (key = 'value')
2)案例
--rename to:
ALTER TABLE hudi_cow_nonpcf_tbl RENAME TO hudi_cow_nonpcf_tbl2;

--add column:
ALTER TABLE hudi_cow_nonpcf_tbl2 add columns(remark string);

--change column:
ALTER TABLE hudi_cow_nonpcf_tbl2 change column uuid uuid int;

--set properties;
alter table hudi_cow_nonpcf_tbl2 set tblproperties (hoodie.keep.max.commits = '10');

修改分区

1)语法

-- Drop Partition
ALTER TABLE tableIdentifier DROP PARTITION ( partition_col_name = partition_col_val [ , ... ] )

-- Show Partitions
SHOW PARTITIONS tableIdentifier

2)案例

--show partition:
show partitions hudi_cow_pt_tbl1;


--drop partition:
alter table hudi_cow_pt_tbl1 drop partition (dt='2021-12-09', hh='10');

注意:show partition结果是基于文件系统表路径的。删除整个分区数据或直接删除某个分区目录并不精确。

存储过程(Procedures)

1)语法

--Call procedure by positional arguments
CALL system.procedure_name(arg_1, arg_2, ... arg_n)

--Call procedure by named arguments
CALL system.procedure_name(arg_name_2 => arg_2, arg_name_1 => arg_1, ... arg_name_n => arg_n)

2)案例
可用的存储过程:https://hudi.apache.org/docs/procedures/

--show commit's info
call show_commits(table => 'hudi_cow_pt_tbl1', limit => 10);
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