BigQuery Subqueries Efficient Join - join

I am trying to analyse firebase analytics data in BigQuery. I need to update a table in BigQuery using StandardSQL.
I have to update order_flag in table cart where key = 'item_id' by joining it to another table order.
Below is the query:
#standardSQL
UPDATE `dataset.cart` c
SET c.order_flag = true
WHERE (SELECT value.string_value
FROM UNNEST(c.event_dim.params)
WHERE key = 'item_id') IN
(SELECT
(SELECT value.string_value
FROM UNNEST(o.event_dim.params)
WHERE key = 'item_id')
FROM `dataset.order` o
WHERE (SELECT key FROM UNNEST(o.event_dim.params)
WHERE key = 'item_id') =
(SELECT value.string_value FROM UNNEST(c.event_dim.params)
WHERE key = 'item_id'))
But I am getting the error:
Error: Correlated subqueries that reference other tables are not supported unless they can be de-correlated, such as by transforming them into an efficient JOIN.
How to do an efficient join in this scenario?

Your query looks a bit strange because it has IN clause with correlated subquery (subquery uses both a and c tables).
Which is kind of antipattern and usually indicates mistake in query. Because normally IN clause subquery is NOT correlated across tables.
EXISTS clause usually requires correlation in subquery, but not IN.
This would work most likely:
UPDATE
`dataset.cart` c
SET
c.order_flag=TRUE
WHERE
(
SELECT
value.string_value
FROM
UNNEST(c.event_dim.params)
WHERE
key = 'item_id') IN (
SELECT
(
SELECT
value.string_value
FROM
UNNEST(o.event_dim.params)
WHERE
key = 'item_id')
FROM
`dataset.order` o
)
If you decide to switch to EXISTS then I would recommend storing
(SELECT
value.string_value
FROM
UNNEST(o.event_dim.params)
WHERE
key = 'item_id')
into separate column to keep things simple and easy to optimize for query optimizer.

Related

Why does Hive warn that this subquery would cause a Cartesian product?

According to Hive's documentation it supports NOT IN subqueries in a WHERE clause, provided that the subquery is an uncorrelated subquery (does not reference columns from the main query).
However, when I attempt to run the trivial query below, I get an error FAILED: SemanticException Cartesian products are disabled for safety reasons.
-- sample data
CREATE TEMPORARY TABLE foods (name STRING);
CREATE TEMPORARY TABLE vegetables (name STRING);
INSERT INTO foods VALUES ('steak'), ('eggs'), ('celery'), ('onion'), ('carrot');
INSERT INTO vegetables VALUES ('celery'), ('onion'), ('carrot');
-- the problematic query
SELECT *
FROM foods
WHERE foods.name NOT IN (SELECT vegetables.name FROM vegetables)
Note that if I use an IN clause instead of a NOT IN clause, it actually works fine, which is perplexing because the query evaluation structure should be the same in either case.
Is there a workaround for this, or another way to filter values from a query based on their presence in another table?
This is Hive 2.3.4 btw, running on an Amazon EMR cluster.
Not sure why you would get that error. One work around is to use not exists.
SELECT f.*
FROM foods f
WHERE NOT EXISTS (SELECT 1
FROM vegetables v
WHERE v.name = f.name)
or a left join
SELECT f.*
FROM foods f
LEFT JOIN vegetables v ON v.name = f.name
WHERE v.name is NULL
You got cartesian join because this is what Hive does in this case. vegetables table is very small (just one row) and it is being broadcasted to perform the cross (most probably map-join, check the plan) join. Hive does cross (map) join first and then applies filter. Explicit left join syntax with filter as #VamsiPrabhala said will force to perform left join, but in this case it works the same, because the table is very small and CROSS JOIN does not multiply rows.
Execute EXPLAIN on your query and you will see what is exactly happening.

Find records with ID in array of IDS and keep the order of records matching that of IDs [duplicate]

I have a simple SQL query in PostgreSQL 8.3 that grabs a bunch of comments. I provide a sorted list of values to the IN construct in the WHERE clause:
SELECT * FROM comments WHERE (comments.id IN (1,3,2,4));
This returns comments in an arbitrary order which in my happens to be ids like 1,2,3,4.
I want the resulting rows sorted like the list in the IN construct: (1,3,2,4).
How to achieve that?
You can do it quite easily with (introduced in PostgreSQL 8.2) VALUES (), ().
Syntax will be like this:
select c.*
from comments c
join (
values
(1,1),
(3,2),
(2,3),
(4,4)
) as x (id, ordering) on c.id = x.id
order by x.ordering
In Postgres 9.4 or later, this is simplest and fastest:
SELECT c.*
FROM comments c
JOIN unnest('{1,3,2,4}'::int[]) WITH ORDINALITY t(id, ord) USING (id)
ORDER BY t.ord;
WITH ORDINALITY was introduced with in Postgres 9.4.
No need for a subquery, we can use the set-returning function like a table directly. (A.k.a. "table-function".)
A string literal to hand in the array instead of an ARRAY constructor may be easier to implement with some clients.
For convenience (optionally), copy the column name we are joining to ("id" in the example), so we can join with a short USING clause to only get a single instance of the join column in the result.
Works with any input type. If your key column is of type text, provide something like '{foo,bar,baz}'::text[].
Detailed explanation:
PostgreSQL unnest() with element number
Just because it is so difficult to find and it has to be spread: in mySQL this can be done much simpler, but I don't know if it works in other SQL.
SELECT * FROM `comments`
WHERE `comments`.`id` IN ('12','5','3','17')
ORDER BY FIELD(`comments`.`id`,'12','5','3','17')
With Postgres 9.4 this can be done a bit shorter:
select c.*
from comments c
join (
select *
from unnest(array[43,47,42]) with ordinality
) as x (id, ordering) on c.id = x.id
order by x.ordering;
Or a bit more compact without a derived table:
select c.*
from comments c
join unnest(array[43,47,42]) with ordinality as x (id, ordering)
on c.id = x.id
order by x.ordering
Removing the need to manually assign/maintain a position to each value.
With Postgres 9.6 this can be done using array_position():
with x (id_list) as (
values (array[42,48,43])
)
select c.*
from comments c, x
where id = any (x.id_list)
order by array_position(x.id_list, c.id);
The CTE is used so that the list of values only needs to be specified once. If that is not important this can also be written as:
select c.*
from comments c
where id in (42,48,43)
order by array_position(array[42,48,43], c.id);
I think this way is better :
SELECT * FROM "comments" WHERE ("comments"."id" IN (1,3,2,4))
ORDER BY id=1 DESC, id=3 DESC, id=2 DESC, id=4 DESC
Another way to do it in Postgres would be to use the idx function.
SELECT *
FROM comments
ORDER BY idx(array[1,3,2,4], comments.id)
Don't forget to create the idx function first, as described here: http://wiki.postgresql.org/wiki/Array_Index
In Postgresql:
select *
from comments
where id in (1,3,2,4)
order by position(id::text in '1,3,2,4')
On researching this some more I found this solution:
SELECT * FROM "comments" WHERE ("comments"."id" IN (1,3,2,4))
ORDER BY CASE "comments"."id"
WHEN 1 THEN 1
WHEN 3 THEN 2
WHEN 2 THEN 3
WHEN 4 THEN 4
END
However this seems rather verbose and might have performance issues with large datasets.
Can anyone comment on these issues?
To do this, I think you should probably have an additional "ORDER" table which defines the mapping of IDs to order (effectively doing what your response to your own question said), which you can then use as an additional column on your select which you can then sort on.
In that way, you explicitly describe the ordering you desire in the database, where it should be.
sans SEQUENCE, works only on 8.4:
select * from comments c
join
(
select id, row_number() over() as id_sorter
from (select unnest(ARRAY[1,3,2,4]) as id) as y
) x on x.id = c.id
order by x.id_sorter
SELECT * FROM "comments" JOIN (
SELECT 1 as "id",1 as "order" UNION ALL
SELECT 3,2 UNION ALL SELECT 2,3 UNION ALL SELECT 4,4
) j ON "comments"."id" = j."id" ORDER BY j.ORDER
or if you prefer evil over good:
SELECT * FROM "comments" WHERE ("comments"."id" IN (1,3,2,4))
ORDER BY POSITION(','+"comments"."id"+',' IN ',1,3,2,4,')
And here's another solution that works and uses a constant table (http://www.postgresql.org/docs/8.3/interactive/sql-values.html):
SELECT * FROM comments AS c,
(VALUES (1,1),(3,2),(2,3),(4,4) ) AS t (ord_id,ord)
WHERE (c.id IN (1,3,2,4)) AND (c.id = t.ord_id)
ORDER BY ord
But again I'm not sure that this is performant.
I've got a bunch of answers now. Can I get some voting and comments so I know which is the winner!
Thanks All :-)
create sequence serial start 1;
select * from comments c
join (select unnest(ARRAY[1,3,2,4]) as id, nextval('serial') as id_sorter) x
on x.id = c.id
order by x.id_sorter;
drop sequence serial;
[EDIT]
unnest is not yet built-in in 8.3, but you can create one yourself(the beauty of any*):
create function unnest(anyarray) returns setof anyelement
language sql as
$$
select $1[i] from generate_series(array_lower($1,1),array_upper($1,1)) i;
$$;
that function can work in any type:
select unnest(array['John','Paul','George','Ringo']) as beatle
select unnest(array[1,3,2,4]) as id
Slight improvement over the version that uses a sequence I think:
CREATE OR REPLACE FUNCTION in_sort(anyarray, out id anyelement, out ordinal int)
LANGUAGE SQL AS
$$
SELECT $1[i], i FROM generate_series(array_lower($1,1),array_upper($1,1)) i;
$$;
SELECT
*
FROM
comments c
INNER JOIN (SELECT * FROM in_sort(ARRAY[1,3,2,4])) AS in_sort
USING (id)
ORDER BY in_sort.ordinal;
select * from comments where comments.id in
(select unnest(ids) from bbs where id=19795)
order by array_position((select ids from bbs where id=19795),comments.id)
here, [bbs] is the main table that has a field called ids,
and, ids is the array that store the comments.id .
passed in postgresql 9.6
Lets get a visual impression about what was already said. For example you have a table with some tasks:
SELECT a.id,a.status,a.description FROM minicloud_tasks as a ORDER BY random();
id | status | description
----+------------+------------------
4 | processing | work on postgres
6 | deleted | need some rest
3 | pending | garden party
5 | completed | work on html
And you want to order the list of tasks by its status.
The status is a list of string values:
(processing, pending, completed, deleted)
The trick is to give each status value an interger and order the list numerical:
SELECT a.id,a.status,a.description FROM minicloud_tasks AS a
JOIN (
VALUES ('processing', 1), ('pending', 2), ('completed', 3), ('deleted', 4)
) AS b (status, id) ON (a.status = b.status)
ORDER BY b.id ASC;
Which leads to:
id | status | description
----+------------+------------------
4 | processing | work on postgres
3 | pending | garden party
5 | completed | work on html
6 | deleted | need some rest
Credit #user80168
I agree with all other posters that say "don't do that" or "SQL isn't good at that". If you want to sort by some facet of comments then add another integer column to one of your tables to hold your sort criteria and sort by that value. eg "ORDER BY comments.sort DESC " If you want to sort these in a different order every time then... SQL won't be for you in this case.

Redshift - Efficient JOIN clause with OR

I have the need to join a huge table (10 million plus rows) to a lookup table (15k plus rows) with an OR condition. Something like:
SELECT t1.a, t1.b, nvl(t1.c, t2.c), nvl(t1.d, t2.d)
FROM table1 t1
JOIN table2 t2 ON t1.c = t2.c OR t1.d = t2.d;
This is because table1 can have c or d as NULL, and I'd like to join on whichever is available, leaving out the rest. The query plan says there is a Nested Loop, which I realize is because of the OR condition. Is there a clean, efficient way of solving this problem? I'm using Redshift.
EDIT: I am trying to run this with a UNION, but it doesn't seem to be any faster than before.
If you have a preferred column you can NVL() (aka COALESCE()) them and join on that.
SELECT t1.a, t1.b, nvl(t1.c, t2.c), nvl(t1.d, t2.d)
FROM table1 t1
JOIN table2 t2
ON t1.c = NVL(t2.c,t2.d);
I'd also suggest that you should set the lookup table to DISTSTYLE ALL to ensure that the larger table is not redistributed.
[ Also, 10 million rows isn't big for Redshift. Not trying to be snotty just saying that we get excellent performance on Redshift even when querying (and joining) tables with hundreds of billions of rows. ]
How about doing two (left) joins? With the small lookup table performance shouldn't be too bad even.
SELECT t1.a, t1.b, nvl(t1.c, t2.c), nvl(t1.d, t3.d)
FROM table1 t1
LEFT JOIN table2 t2 ON t1.d = t2.d and t1.c is null
LEFT JOIN table2 t3 ON t1.c = t3.c and t1.d is null
Your original query only returns rows that match at least one of c or d in the lookup table. If that's not guaranteed you may need to add filters...for example rows in t1 where both c and d are null or have values not present in table2.
Don't really need the null checks in the joins, but might be slightly faster.

Hive: Not in subquery join

I'm looking for a way to select all values from one table which do no exits in other table. This needs to be done on two variables, not one.
select * from tb1
where tb1.id1 not in (select id1 from tb2)
and tb1.id2 not in (select id2 from tb2)
I cannot use subquery. It needs to be done using joins only.
I tried this:
select * from tb1 full join tb2 on
tb1.id1=tb2.id1 and tb1.id2=tb2.id2
This works fine with one variable in condition, but not two.
Please suggest some resolution.
Since you are looking to get all the data from tb1 with no common data on columns id1 and id2 on tb2, You can use a left outer join on table tb1. Something like
SELECT tb1.* FROM tb1 LEFT OUTER JOIN tb2 ON
(tb1.id1=tb2.id1 AND tb1.id2=tb2.id2)
WHERE tb2.id1 IS NULL

Hive Join returning zero records

I have two Hive tables and I am trying to join both of them. The tables are not clustered or partitioned by any field. Though the tables contain records for common key fields, the join query always returns 0 records. All the data types are 'string' data types.
The join query is simple and looks something like below
select count(*) cnt
from
fsr.xref_1 A join
fsr.ipfile_1 B
on
(
A.co_no = B.co_no
)
;
Any idea what could be going wrong? I have just one record (same value) in both the tables.
Below are my table definitions
CREATE TABLE xref_1
(
co_no string
)
clustered by (co_no) sorted by (co_no asc) into 10 buckets
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
LINES TERMINATED BY '\n'
STORED AS TEXTFILE;
CREATE TABLE ipfile_1
(
co_no string
)
clustered by (co_no) sorted by (co_no asc) into 10 buckets
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
LINES TERMINATED BY '\n'
STORED AS TEXTFILE;
Hi You are using Star Schema Join. Please use your query like this:
SELET COUNT(*) cnt FROM A a JOIN B b ON (a.key1 = b.key1);
If still have issue Then use MAPJOIN:
set hive.auto.convert.join=true;
select count(*) from A join B on (key1 = key2)
Please see Link for more detail.

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