There are lots of data coming from multiple sources that I need to group based on priority, but the data quality from those sources is different - they may be missing some data.
The task is to group that data into a separate table, in as complete as possible way.
For example:
create table grouped_data (
id serial primary key,
type text,
a text,
b text,
c int
);
create table raw_data (
id serial primary key,
type text,
a text,
b text,
c int,
priority int
);
insert into raw_data
(type, a, b, c, priority)
values
('one', null, '', 123, 1),
('one', 'foo', '', 456, 2),
('one', 'bar', 'baz', 789, 3),
('two', null, 'two-b', 11, 3),
('two', '', '', 33, 2),
('two', null, 'two-bbb', 22, 1);
Now I need to group records by type, order by priority, take the first non-null and non-empty value, and put it into grouped_data.
In this case, value of a for group one would be foo because the row that holds that value have a higher priority than the one with bar. And c should be 123, as it has the highest prio.
Same for group two, for each column we take the data that is non-null, non-empty, and has the highest priority, or fallback to null if no actual data present.
In the end, grouped_data is expected to have the following content:
('one', 'foo', 'baz', 123),
('two', null, 'two-bbb', 22)
I've tried grouping, sub-selects, MERGE, cross joins... Alas, my knowledge of PostgreSQL is not good enough to get it working.
One thing I'd like to avoid, too - is going through columns one-by-one, since in the real world there are few dozens of columns to work with...
A link to a fiddle I've been using to mess around with this: http://sqlfiddle.com/#!17/76699/1
UPD:
Thank you all!
Oleksii Tambovtsev's solution is the fastest one. On a set of data closely resembling a real-world case (2m records, ~30 fields) it takes only 20 seconds to produce the exact same set of data, which was previously generated programmatically and took over 20 minutes.
eshirvana's solution does the same in 95s, Steve Kass' in 125s, and Stefanov.sm - 308s (which is still helluvalotfaster than programatically!)
Thank you all :)
You should try this:
SELECT
type,
(array_agg(a ORDER BY priority ASC) FILTER (WHERE a IS NOT NULL AND a != ''))[1] as a,
(array_agg(b ORDER BY priority ASC) FILTER (WHERE b IS NOT NULL AND b != ''))[1] as b,
(array_agg(c ORDER BY priority ASC) FILTER (WHERE c IS NOT NULL))[1] as c
FROM raw_data GROUP BY type ORDER BY type;
you can use window function first_value:
select distinct
type
, first_value(a) over (partition by type order by nullif(a,'') is null, priority) as a
, first_value(b) over (partition by type order by nullif(b,'') is null, priority) as b
, first_value(c) over (partition by type order by priority) as c
from raw_data
select distinct on (type) type,
first_value(a) over (partition by type order by (nullif(a, '') is null), priority) a,
first_value(b) over (partition by type order by (nullif(b, '') is null), priority) b,
first_value(c) over (partition by type order by (c is null), priority) c
from raw_data;
This should also work.
WITH types(type) AS (
SELECT DISTINCT
type
FROM raw_data
)
SELECT
type,
(SELECT a FROM raw_data WHERE a > '' AND raw_data.type = types.type ORDER BY priority LIMIT 1) AS a,
(SELECT b FROM raw_data WHERE b > '' AND raw_data.type = types.type ORDER BY priority LIMIT 1) AS b,
(SELECT c FROM raw_data WHERE c IS NOT NULL AND raw_data.type = types.type ORDER BY priority LIMIT 1) AS c
FROM types
ORDER BY type;
Related
I am looking to join two time-ordered tables, such that the events in table1 are matched to the "next" event in table2 (within the same user). I am using SQL / Snowflake for this.
For argument's sake table1 is "notification_clicked" events and table2 is "purchases"
This is one way to do it:
WITH partial_result AS (
SELECT
userId, notificationId, notificationTimeStamp, transactionId, transactionTimeStamp
FROM table1 CROSS JOIN table2
WHERE table1.userId = table2.userId
AND notificationTimeStamp <= transactionTimeStamp)
SELECT *
FROM partial_result
QUALIFY ROW_NUMBER() OVER(
PARTITION BY userId, notificationId ORDER BY transactionTimeStamp ASC
) = 1
It is not super readable, but is this "the" way to do this?
If you're doing an AsOf join against small tables, you can use a regular Venn diagram type of join. If you're running it against large tables, a regular join will lead to an intermediate cardinality explosion before the filter.
For large tables, this is the highest performance approach I have to date. Rather than treating an AsOf join like a regular Venn diagram join, we can treat it like a special type of union between two tables with a filter that uses the information from that union. The sample SQL does the following:
Unions the A and B tables so that the Entity and Time come from both tables and all other columns come from only one table. Rows from the other table specify NULL for these values (measures 1 and 2 in this case). It also projects a source column for the table. We'll use this later.
In the unioned table, it uses a LAG function on windows partitioned by the Entity and ordered by the Time. For each row with a source indicator from the A table, it lags back to the first Time with source in the B table, ignoring all values in the A table.
with A as
(
select
COLUMN1::int as "E", -- Entity
COLUMN2::int as "T", -- Time
COLUMN4::string as "M1" -- Measure (could be many)
from (values
(1, 7, 1, 'M1-1'),
(1, 8, 1, 'M1-2'),
(1, 41, 1, 'M1-3'),
(1, 89, 1, 'M1-4')
)
), B as
(
select
COLUMN1::int as "E", -- Entity
COLUMN2::int as "T", -- Time
COLUMN4::string as "M2" -- Different measure (could be many)
from (values
(1, 6, 1, 'M2-1'),
(1, 12, 1, 'M2-2'),
(1, 20, 1, 'M2-3'),
(1, 35, 1, 'M2-4'),
(1, 57, 1, 'M2-5'),
(1, 85, 1, 'M2-6'),
(1, 92, 1, 'M2-7')
)
), UNIONED as -- Unify schemas and union all
(
select 'A' as SOURCE_TABLE -- Project the source table
,E as AB_E -- AB_ means it's unified
,T as AB_T
,M1 as A_M1 -- A_ means it's from A
,NULL::string as B_M2 -- Make columns from B null for A
from A
union all
select 'B' as SOURCE_TABLE
,E as AB_E
,T as AB_T
,NULL::string as A_M1 -- Make columns from A null for B
,M2 as B_M2
from B
)
select AB_E as ENTITY
,AB_T as A_TIME
,lag(iff(SOURCE_TABLE = 'A', null, AB_T)) -- Lag back to
ignore nulls over -- previous B row
(partition by AB_E order by AB_T) as B_TIME
,A_M1 as M1_FROM_A
,lag(B_M2) -- Lag back to the previous non-null row.
ignore nulls -- The A sourced rows will already be NULL.
over (partition by AB_E order by AB_T) as M2_FROM_B
from UNIONED
qualify SOURCE_TABLE = 'A'
;
This will perform orders of magnitude faster for large tables because the highest intermediate cardinality is guaranteed to be the cardinality of A + B.
To simplify this refactor, I wrote a stored procedure that generates the SQL given the paths to table A and B, the entity column in A and B (right now limited to one, but if you have more it will get the SQL started), the order by (time) column in A and B, and finally the list of columns to "drag through" the AsOf join. It's rather lengthy so I posted it on Github and will work later to document and enhance it:
https://github.com/GregPavlik/AsOfJoin/blob/main/StoredProcedure.sql
I am trying to join several tables. To simplify the situation, there is a table called Boxes which has a foreign key column for another table, Requests. This means that with a simple join I can get all the boxes that can be used to fulfill a request. But the Requests table also has a column called BoxCount which limits the number of boxes that is needed.
Is there a way to structure the query in such a way that when I join the two tables, I will only get the number of rows from Boxes that is specified in the BoxCount column of the given Request, rather than all of the rows from Boxes that have a matching foreign key?
Script to initialize sample data:
CREATE TABLE Requests (
Id int NOT NULL PRIMARY KEY,
BoxCount Int NOT NULL);
CREATE TABLE Boxes (
Id int NOT NULL PRIMARY KEY,
Label varchar,
RequestId INT FOREIGN KEY REFERENCES Requests(Id));
INSERT INTO Requests (Id, BoxCount)
VALUES
(1, 2),
(2, 3);
INSERT INTO Boxes (Id, Label, RequestId)
VALUES
(1, 'A', 1),
(2, 'B', 1),
(3, 'C', 1),
(4, 'D', 2),
(5, 'E', 2),
(6, 'F', 2),
(7, 'G', 2);
So, for example, when the hypothetical query is ran, it should return boxes A and B (because the first Request only needs 2 boxes), but not C. Similarly it should also include boxes D, E and F, but not box G, because the second request only requires 3 boxes.
Here is another approach using ROWCOUNT - a common and useful technique that every sql writer should master. The idea here is that you create a sequential number for all boxes within a request and use that to compare to the box count for filtering.
with boxord as (select *,
ROW_NUMBER() OVER (PARTITION BY RequestId ORDER BY Id) as rno
from dbo.Boxes
)
select req.*, boxord.Label, boxord.rno
from dbo.Requests as req inner join boxord on req.Id = boxord.RequestId
where req.BoxCount >= boxord.rno
order by req.Id, boxord.rno
;
fiddle to demonstrate
The INNER JOIN keyword selects records that have matching values in both tables
SELECT (cols) FROM Boxes
INNER JOIN Request on Boxes.(FK_column) = request.id
WHERE Request.BoxCount = (value)
select r.id,
r.boxcount,
b.id,
b.label
from requests r
cross apply (
select top (r.BoxCount)
id, label
from boxes
where requestid = r.id
order by id
) b;
I have a table in SQL Server that stores geology samples, and there is a rule that must be adhered to.
The rule is simple, a "DUP_2" sample must always come after a "DUP_1" sample (sometimes they are loaded inverted)
CREATE TABLE samples (
id INT
,name VARCHAR(5)
);
INSERT INTO samples VALUES (1, 'ASSAY');
INSERT INTO samples VALUES (2, 'DUP_1');
INSERT INTO samples VALUES (3, 'DUP_2');
INSERT INTO samples VALUES (4, 'ASSAY');
INSERT INTO samples VALUES (5, 'DUP_2');
INSERT INTO samples VALUES (6, 'DUP_1');
INSERT INTO samples VALUES (7, 'ASSAY');
id
name
1
ASSAY
2
DUP_1
3
DUP_2
4
ASSAY
5
DUP_2
6
DUP_1
7
ASSAY
In this example I would like to show all rows where name equal to 'DUP_2' and predecessor row (using ID) name is different from 'DUP_1'.
In this case, it would be row 5 only.
I would appreciate very much if you help me.
You can use the LAG() window function or you can use LEAD() - they are identical except for the way in which they are ordered. That is - LAG(name) OVER ( ORDER BY id ) is the same as LEAD(name) OVER ( ORDER BY id DESC ). (You can read more about these functions here.)
WITH s1 ( id, name, prior_name ) AS (
SELECT id, name, LAG(name) OVER ( ORDER BY id ) AS prior_name
FROM samples
)
SELECT id, name
FROM s1
WHERE name = 'DUP_2'
AND COALESCE(prior_name, 'DUMMY') != 'DUP_1';
The reason for the COALESCE() at the end with the DUMMY value is that the first value won't have a LAG(); it will be NULL; and we want to return the DUP_2 record in this case since it doesn't follow a DUP_1 record.
You can use lag():
select s.*
from (select s.*,
lag(name) over (order by id) as prev_name
from samples s
) s
where name = 'DUP_2' and (prev_name <> 'DUP_1' or prev_name is null)
I would like to filter an aggregated array depending on all values associated with an id. The values are strings and can be of three type all-x:y, x:y and empty (here x and y are arbitrary substrings of values).
I have a few conditions:
If an id has x:y then the result should contain x:y.
If an id always has all-x:y then the resulting aggregation should have all-x:y
If an id sometimes has all-x:y then the resulting aggregation should have x:y
For example with the following
WITH
my_table(id, my_values) AS (
VALUES
(1, ['all-a','all-b']),
(2, ['all-c','b']),
(3, ['a','b','c']),
(1, ['all-a']),
(2, []),
(3, ['all-c']),
),
The result should be:
(1, ['all-a','b']),
(2, ['c','b']),
(3, ['a','b','c']),
I have worked multiple hours on this but it seems like it's not feasible.
I came up with the following but it feels like it cannot work because I can check the presence of all-x in all arrays which would go in <<IN ALL>>:
SELECT
id,
SET_UNION(
CASE
WHEN SPLIT_PART(my_table.values,'-',1) = 'all' THEN
CASE
WHEN <<my_table.values IN ALL>> THEN my_table.values
ELSE REPLACE(my_table.values,'all-')
END
ELSE my_table.values
END
) AS values
FROM my_table
GROUP BY 1
I would need to check that all arrays values for the specific id contains all-x and that's where I'm struggling to find a solution.
I was trying to co
After a few hours of searching how to do so I am starting to believe that it is not feasible.
Any help is appreciated. Thank you for reading.
This should do what you want:
WITH my_table(id, my_values) AS (
VALUES
(1, array['all-a','all-b']),
(2, array['all-c','b']),
(3, array['a','b','c']),
(1, array['all-a']),
(2, array[]),
(3, array['all-c'])
),
with_group_counts AS (
SELECT *, count(*) OVER (PARTITION BY id) group_count -- to see if the number of all-X occurrences match the number of rows for a given id
FROM my_table
),
normalized AS (
SELECT
id,
if(
count(*) OVER (PARTITION BY id, value) = group_count AND starts_with(value, 'all-'), -- if its an all-X value and every original row for the given id contains it ...
value,
if(starts_with(value, 'all-'), substr(value, 5), value)) AS extracted
FROM with_group_counts CROSS JOIN UNNEST(with_group_counts.my_values) t(value)
)
SELECT id, array_agg(DISTINCT extracted)
FROM normalized
GROUP BY id
The trick is to compute the number of total rows for each id in the original table via the count(*) OVER (PARTITION BY id) expression in the with_group_counts subquery. We can then use that value to determine whether a given value should be treated as an all-x or the x should be extracted. That's handled by the following expression:
if(
count(*) OVER (PARTITION BY id, value) = group_count AND starts_with(value, 'all-'),
value,
if(starts_with(value, 'all-'), substr(value, 5), value))
For more information about window functions in Presto, check out the documentation. You can find the documentation for UNNEST here.
In SQL Server, I have a table where a column A stores some data. This data can contain duplicates (ie. two or more rows will have the same value for the column A).
I can easily find the duplicates by doing:
select A, count(A) as CountDuplicates
from TableName
group by A having (count(A) > 1)
Now, I want to retrieve the values of other columns, let's say B and C. Of course, those B and C values can be different even for the rows sharing the same A value, but it doesn't matter for me. I just want any B value and any C one, the first, the last or the random one.
If I had a small table and one or two columns to retrieve, I would do something like:
select A, count(A) as CountDuplicates, (
select top 1 child.B from TableName as child where child.A = base.A) as B
)
from TableName as base group by A having (count(A) > 1)
The problem is that I have much more rows to get, and the table is quite big, so having several children selects will have a high performance cost.
So, is there a less ugly pure SQL solution to do this?
Not sure if my question is clear enough, so I give an example based on AdventureWorks database. Let's say I want to list available States, and for each State, get its code, a city (any city) and an address (any address). The easiest, and the most inefficient way to do it would be:
var q = from c in data.StateProvinces select new { c.StateProvinceCode, c.Addresses.First().City, c.Addresses.First().AddressLine1 };
in LINQ-to-SQL and will do two selects for each of 181 States, so 363 selects. I my case, I am searching for a way to have a maximum of 182 selects.
The ROW_NUMBER function in a CTE is the way to do this. For example:
DECLARE #mytab TABLE (A INT, B INT, C INT)
INSERT INTO #mytab ( A, B, C ) VALUES (1, 1, 1)
INSERT INTO #mytab ( A, B, C ) VALUES (1, 1, 2)
INSERT INTO #mytab ( A, B, C ) VALUES (1, 2, 1)
INSERT INTO #mytab ( A, B, C ) VALUES (1, 3, 1)
INSERT INTO #mytab ( A, B, C ) VALUES (2, 2, 2)
INSERT INTO #mytab ( A, B, C ) VALUES (3, 3, 1)
INSERT INTO #mytab ( A, B, C ) VALUES (3, 3, 2)
INSERT INTO #mytab ( A, B, C ) VALUES (3, 3, 3)
;WITH numbered AS
(
SELECT *, rn=ROW_NUMBER() OVER (PARTITION BY A ORDER BY B, C)
FROM #mytab AS m
)
SELECT *
FROM numbered
WHERE rn=1
As I mentioned in my comment to HLGEM and Philip Kelley, their simple use of an aggregate function does not necessarily return one "solid" record for each A group; instead, it may return column values from many separate rows, all stitched together as if they were a single record. For example, if this were a PERSON table, with the PersonID being the "A" column, and distinct contact records (say, Home and Word), you might wind up returning the person's home city, but their office ZIP code -- and that's clearly asking for trouble.
The use of the ROW_NUMBER, in conjunction with a CTE here, is a little difficult to get used to at first because the syntax is awkward. But it's becoming a pretty common pattern, so it's good to get to know it.
In my sample I've define a CTE that tacks on an extra column rn (standing for "row number") to the table, that itself groups by the A column. A SELECT on that result, filtering to only those having a row number of 1 (i.e., the first record found for that value of A), returns a "solid" record for each A group -- in my example above, you'd be certain to get either the Work or Home address, but not elements of both mixed together.
It concerns me that you want any old value for fields b and c. If they are to be meaningless why are you returning them?
If it truly doesn't matter (and I honestly can't imagine a case where I would ever want this, but it's what you said) and the values for b and c don't even have to be from the same record, group by with the use of mon or max is the way to go. It's more complicated if you want the values for a particular record for all fields.
select A, count(A) as CountDuplicates, min(B) as B , min(C) as C
from TableName as base
group by A
having (count(A) > 1)
you can do some thing like this if you have id as primary key in your table
select id,b,c from tablename
inner join
(
select id, count(A) as CountDuplicates
from TableName as base group by A,id having (count(A) > 1)
)d on tablename.id= d.id