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CREATE SCHEDULED QUERY <scheduled_query_name>
<scheduleSpecification>
[<executedAsSpec> ]
[<enableSpecification>]
<definedAsSpec>
Alter Scheduled query syntax
ALTER SCHEDULED QUERY <scheduled_query_name>
(<scheduleSpec>|<executedAsSpec>|<enableSpecification>|<definedAsSpec>|<executeSpec>);
Drop syntax
DROP SCHEDULED QUERY <scheduled_query_name>;
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CRON <quartz_schedule_expression>
where
quartz_schedule_expression is quoted schedule in the Quartz format Anchor quartz_schedule_expression quartz_schedule_expression
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Note |
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For CREATE SCHEDULED QUERY statements the default behaviour is set by the configuration key hive.scheduled.queries.create.as.enabled |
Note |
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In case there are in-flight scheduled executions at the time when the corresponding schedule is disabled - the already running executions will still finish. But no more executions will be triggered. |
AnchordefinedAsSpec definedAsSpec
Defined AS syntax
definedAsSpec | |
definedAsSpec |
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The “query” is a single statement expression to be scheduled for execution.
System tables/views
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EXECUTE
Changes the schedules next execution time to be now. Could be useful during debugging/development.
System tables/views
Informations about scheduled queries/executions can be obtain by Informations about scheduled queries/executions can be obtain by using the information_schema or the sysdb - recommended way is to use the information_schema; sysdb is tables are there to build the information_schema level views - and for debugging.
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- hive.scheduled.queries.executor.enabled (default: true)
Controls whether HS2 will run scheduled query executor. - hive.scheduled.queries.namespace (default: "hive")
Sets the scheduled query namespace to be used. New scheduled queries are created in this namespace; and execution is also bound to the namespace - hive.scheduled.queries.executor.idle.sleep.time (default: 1 minute)
Time to sleep between querying for the presence of a scheduled query. - hive.scheduled.queries.executor.progress.report.interval (default: 1 minute)
While scheduled queries are in flight; a background update happens periodically to report the actual state of the query. - hive.scheduled.queries.create.as.enabled (default: true)
This option sets the default behaviour of newly created scheduled queries. - hive.security.authorization.scheduled.queries.supported (default: false)
Enable this if the configured authorizer is able to handle scheduled query related calls.
Examples
Example 1 – basic example of using schedules
Code Block |
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create table t (a integer); |
...
-- create a scheduled query; every 10 minute insert a new row create scheduled query sc1 cron '0 */10 * * * ? * |
...
' as insert into t values (1); |
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Example 1 - general usage of schedules
create table t (a integer);
-- create scheduled queries
create scheduled query sc1 cron ‘0 */10 * * * ? *’ as insert into t values (1);
...
-- depending on hive.scheduled.queries.create.as.enabled the query might get create in disabled mode |
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-- it can be enabled using: |
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alter scheduled query sc1 enabled; |
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-- inspect scheduled queries using the information_schema select * from information_schema |
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.scheduled_queries s where schedule_name='sc1';
+-----------------------+------------------+------------+----------------------+-------------------+---------+-----------+----------------------+
| s.scheduled_query_id | s.schedule_name | s.enabled | s.cluster_namespace | s.schedule | s.user | s.query | s.next_execution |
+-----------------------+------------------+------------+----------------------+-------------------+---------+-----------+----------------------+
| 1 | sc1 | true | hive | 0 */10 * * * ? * | dev | select 1 | 2020-02-03 15:10:00 |
+-----------------------+------------------+------------+----------------------+-------------------+---------+-----------+----------------------+
-- wait 10 minutes or execute by issuing:
alter scheduled query sc1 execute;
select * from information_schema.scheduled_executions s where schedule_name='sc1' order by scheduled_execution_id desc limit 1;
+---------------------------+------------------+----------------------------------------------------+-----------+----------------------+----------------------+------------+------------------+---------------------+
| s.scheduled_execution_id | s.schedule_name | s.executor_query_id | s.state | s.start_time | s.end_time | s.elapsed | s.error_message | s.last_update_time |
+---------------------------+------------------+----------------------------------------------------+-----------+----------------------+----------------------+------------+------------------+---------------------+
| 496 | sc1 | dev_20200203152025_bdf3deac-0ca6-407f-b122-c637e50f99c8 | FINISHED | 2020-02-03 15:20:23 | 2020-02-03 15:20:31 | 8 | NULL | NULL |
+---------------------------+------------------+----------------------------------------------------+-----------+----------------------+----------------------+------------+------------------+---------------------+
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Example 2 – analyze external table periodically
Suppose you have an external table - the contents of it is slowly changing...which will eventually lead that Hive will utilize outdated statistics during planning time
Code Block |
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-- create external table
create external table t (a integer);
-- see where the table lives:
desc formatted t;
[...]
| Location: | file:/data/hive/warehouse/t | NULL |
[...]
-- in a terminal; load some data into the table directory:
seq 1 10 > /data/hive/warehouse/t/f1
-- back in hive you will see that
select count(1) from t;
10
-- meanwhile basic stats show that the table has "0" rows
desc formatted t;
[...]
| | numRows | 0 |
[...]
create scheduled query t_analyze cron '0 */1 * * * ? *' as analyze table t compute statistics for columns;
-- wait some time or execute by issuing:
alter scheduled query t_analyze execute;
select * from information_schema.scheduled_executions s where schedule_name='ex_analyze' order by scheduled_execution_id desc limit 3;
+---------------------------+------------------+----------------------------------------------------+------------+----------------------+----------------------+------------+------------------+----------------------+
| s.scheduled_execution_id | s.schedule_name | s.executor_query_id | s.state | s.start_time | s.end_time | s.elapsed | s.error_message | s.last_update_time |
+---------------------------+------------------+----------------------------------------------------+------------+----------------------+----------------------+------------+------------------+----------------------+
| 498 | t_analyze | dev_20200203152640_a59bc198-3ed3-4ef2-8f63-573607c9914e | FINISHED | 2020-02-03 15:26:38 | 2020-02-03 15:28:01 | 83 | NULL | NULL |
+---------------------------+------------------+----------------------------------------------------+------------+----------------------+----------------------+------------+------------------+----------------------+
-- and the numrows have been updated
desc formatted t;
[...]
| | numRows | 10 |
[...]
-- we don't want this running every minute anymore...
alter scheduled query t_analyze disable; |
Example 3 – materialized view rebuild
Code Block |
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-- some settings...they might be there already
set hive.support.concurrency=true;
set hive.txn.manager=org.apache.hadoop.hive.ql.lockmgr.DbTxnManager;
set hive.strict.checks.cartesian.product=false;
set hive.stats.fetch.column.stats=true;
set hive.materializedview.rewriting=true;
-- create some tables
CREATE TABLE emps (
empid INT,
deptno INT,
name VARCHAR(256),
salary FLOAT,
hire_date TIMESTAMP)
STORED AS ORC
TBLPROPERTIES ('transactional'='true');
CREATE TABLE depts (
deptno INT,
deptname VARCHAR(256),
locationid INT)
STORED AS ORC
TBLPROPERTIES ('transactional'='true');
-- load data
insert into emps values (100, 10, 'Bill', 10000, 1000), (200, 20, 'Eric', 8000, 500),
(150, 10, 'Sebastian', 7000, null), (110, 10, 'Theodore', 10000, 250), (120, 10, 'Bill', 10000, 250),
(1330, 10, 'Bill', 10000, '2020-01-02');
insert into depts values (10, 'Sales', 10), (30, 'Marketing', null), (20, 'HR', 20);
insert into emps values (1330, 10, 'Bill', 10000, '2020-01-02');
-- create mv
CREATE MATERIALIZED VIEW mv1 AS
SELECT empid, deptname, hire_date FROM emps
JOIN depts ON (emps.deptno = depts.deptno)
WHERE hire_date >= '2016-01-01 00:00:00';
EXPLAIN
SELECT empid, deptname FROM emps
JOIN depts ON (emps.deptno = depts.deptno)
WHERE hire_date >= '2018-01-01';
-- create a schedule to rebuild mv
create scheduled query mv_rebuild cron '0 */10 * * * ? *' defined as
alter materialized view mv1 rebuild;
-- from this expalin it will be seen that the mv1 is being used
EXPLAIN
SELECT empid, deptname FROM emps
JOIN depts ON (emps.deptno = depts.deptno)
WHERE hire_date >= '2018-01-01';
-- insert a new record
insert into emps values (1330, 10, 'Bill', 10000, '2020-01-02');
-- the source tables are scanned
EXPLAIN
SELECT empid, deptname FROM emps
JOIN depts ON (emps.deptno = depts.deptno)
WHERE hire_date >= '2018-01-01';
-- wait 10 minutes or execute
alter scheduled query mv_rebuild execute;
-- run it again...the view should be rebuilt
EXPLAIN
SELECT empid, deptname FROM emps
JOIN depts ON (emps.deptno = depts.deptno)
WHERE hire_date >= '2018-01-01';
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Example 4 – Ingestion
Code Block |
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drop table if exists t;
drop table if exists s;
-- suppose that this table is an external table or something
-- which supports the pushdown of filter condition on the id column
create table s(id integer, cnt integer);
-- create an internal table and an offset table
create table t(id integer, cnt integer);
create table t_offset(offset integer);
insert into t_offset values(0);
-- pretend that data is added to s
insert into s values(1,1);
-- run an ingestion...
from (select id==offset as first,* from s
join t_offset on id>=offset) s1
insert into t select id,cnt where first = false
insert overwrite table t_offset select max(s1.id);
-- configure to run ingestion every 10 minutes
create scheduled query ingest every 10 minutes defined as
from (select id==offset as first,* from s
join t_offset on id>=offset) s1
insert into t select id,cnt where first = false
insert overwrite table t_offset select max(s1.id);
-- add some new values
insert into s values(2,2),(3,3);
-- pretend that a timeout have happened
alter scheduled query ingest execute;
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