NTH in Legacy SQL in BigQuery doesn't work as expected - google-bigquery

I have this query written in Legacy SQL:
select
nth(1, a) first_a,
nth(1, b) first_b
from (
select *
from
(select 12 a, null b),
(select null a, 54 b)
)
As a result I was expecting one row with values (12, null), but I got (12, 54) instead. In the documentation for NTH it says:
NTH(n, field)
Returns the nth sequential value in the scope of the function, where n
is a constant. The NTH function starts counting at 1, so there is no
zeroth term. If the scope of the function has less than n values, the
function returns NULL.
There is nothing indicating that nulls would be ignored.
Is this a bug in BigQuery?

This is the important part in the documentation:
in the scope of the function
The scope is normally a "record" (in legacy SQL terms), where you fetch the nth value within a repeated field. As written, though, this query has the effect of using NTH as an aggregate function. The values in the group have no well-defined order, but it so happens that NULL is ordered after the non-null values, so NTH(1, ...) gives a non-null value. Try using 2 as the ordinal instead, for instance:
select
nth(2, a) first_a,
nth(2, b) first_b
from (
select *
from
(select 12 a, null b),
(select null a, 54 b)
)
This returns null, null as output.
With that said, to ensure well-defined semantics in your queries, the best option is to use standard SQL instead. Some analogues to the NTH operator when using standard SQL are:
The array bracket operator, e.g. array_column[OFFSET(0)] to get the first element in an array.
The NTH_VALUE window function, e.g. NTH_VALUE(x, 1) OVER (PARTITION BY y ORDER BY z). See also FIRST_VALUE and LAST_VALUE.

Related

Bigquery SQL: convert array to columns

I have a table with a field A where each entry is a fixed length array A of integers (say length=1000). I want to know how to convert it into 1000 columns, with column name given by index_i, for i=0,1,2,...,999, and each element is the corresponding integer. I can have it done by something like
A[OFFSET(0)] as index_0,
A[OFFSET(1)] as index_1
A[OFFSET(2)] as index_2,
A[OFFSET(3)] as index_3,
A[OFFSET(4)] as index_4,
...
A[OFFSET(999)] as index_999,
I want to know what would be an elegant way of doing this. thanks!
The first thing to say is that, sadly, this is going to be much more complicated than most people expect. It can be conceptually easier to pass the values into a scripting language (e.g. Python) and work there, but clearly keeping things inside BigQuery is going to be much more performant. So here is an approach.
Cross-joining to turn array fields into long-format tables
I think the first thing you're going to want to do is get the values out of the arrays and into rows.
Typically in BigQuery this is accomplished using CROSS JOIN. The syntax is a tad unintuitive:
WITH raw AS (
SELECT "A" AS name, [1,2,3,4,5] AS a
UNION ALL
SELECT "B" AS name, [5,4,3,2,1] AS a
),
long_format AS (
SELECT name, vals
FROM raw
CROSS JOIN UNNEST(raw.a) AS vals
)
SELECT * FROM long_format
UNNEST(raw.a) is taking those arrays of values and turning each array into a set of (five) rows, every single one of which is then joined to the corresponding value of name (the definition of a CROSS JOIN). In this way we can 'unwrap' a table with an array field.
This will yields results like
name | vals
-------------
A | 1
A | 2
A | 3
A | 4
A | 5
B | 5
B | 4
B | 3
B | 2
B | 1
Confusingly, there is a shorthand for this syntax in which CROSS JOIN is replaced with a simple comma:
WITH raw AS (
SELECT "A" AS name, [1,2,3,4,5] AS a
UNION ALL
SELECT "B" AS name, [5,4,3,2,1] AS a
),
long_format AS (
SELECT name, vals
FROM raw, UNNEST(raw.a) AS vals
)
SELECT * FROM long_format
This is more compact but may be confusing if you haven't seen it before.
Typically this is where we stop. We have a long-format table, created without any requirement that the original arrays all had the same length. What you're asking for is harder to produce - you want a wide-format table containing the same information (relying on the fact that each array was the same length.
Pivot tables in BigQuery
The good news is that BigQuery now has a PIVOT function! That makes this kind of operation possible, albeit non-trivial:
WITH raw AS (
SELECT "A" AS name, [1,2,3,4,5] AS a
UNION ALL
SELECT "B" AS name, [5,4,3,2,1] AS a
),
long_format AS (
SELECT name, vals, offset
FROM raw, UNNEST(raw.a) AS vals WITH OFFSET
)
SELECT *
FROM long_format PIVOT(
ANY_VALUE(vals) AS vals
FOR offset IN (0,1,2,3,4)
)
This makes use of WITH OFFSET to generate an extra offset column (so that we know which order the values in the array originally had).
Also, in general pivoting requires us to aggregate the values returned in each cell. But here we expect exactly one value for each combination of name and offset, so we simply use the aggregation function ANY_VALUE, which non-deterministically selects a value from the group you're aggregating over. Since, in this case, each group has exactly one value, that's the value retrieved.
The query yields results like:
name vals_0 vals_1 vals_2 vals_3 vals_4
----------------------------------------------
A 1 2 3 4 5
B 5 4 3 2 1
This is starting to look pretty good, but we have a fundamental issue, in that the column names are still hard-coded. You wanted them generated dynamically.
Unfortunately expressions for the pivot column values aren't something PIVOT can accept out-of-the-box. Note that BigQuery has no way to know that your long-format table will resolve neatly to a fixed number of columns (it relies on offset having the values 0-4 for each and every set of records).
Dynamically building/executing the pivot
And yet, there is a way. We will have to leave behind the comfort of standard SQL and move into the realm of BigQuery Procedural Language.
What we must do is use the expression EXECUTE IMMEDIATE, which allows us to dynamically construct and execute a standard SQL query!
(as an aside, I bet you - OP or future searchers - weren't expecting this rabbit hole...)
This is, of course, inelegant to say the least. But here is the above toy example, implemented using EXECUTE IMMEDIATE. The trick is that the executed query is defined as a string, so we just have to use an expression to inject the full range of values you want into this string.
Recall that || can be used as a string concatenation operator.
EXECUTE IMMEDIATE """
WITH raw AS (
SELECT "A" AS name, [1,2,3,4,5] AS a
UNION ALL
SELECT "B" AS name, [5,4,3,2,1] AS a
),
long_format AS (
SELECT name, vals, offset
FROM raw, UNNEST(raw.a) AS vals WITH OFFSET
)
SELECT *
FROM long_format PIVOT(
ANY_VALUE(vals) AS vals
FOR offset IN ("""
|| (SELECT STRING_AGG(CAST(x AS STRING)) FROM UNNEST(GENERATE_ARRAY(0,4)) AS x)
|| """
)
)
"""
Ouch. I've tried to make that as readable as possible. Near the bottom there is an expression that generates the list of column suffices (pivoted values of offset):
(SELECT STRING_AGG(CAST(x AS STRING)) FROM UNNEST(GENERATE_ARRAY(0,4)) AS x)
This generates the string "0,1,2,3,4" which is then concatenated to give us ...FOR offset IN (0,1,2,3,4)... in our final query (as in the hard-coded example before).
REALLY dynamically executing the pivot
It hasn't escaped my notice that this is still technically insisting on your knowing up-front how long those arrays are! It's a big improvement (in the narrow sense of avoiding painful repetitive code) to use GENERATE_ARRAY(0,4), but it's not quite what was requested.
Unfortunately, I can't provide a working toy example, but I can tell you how to do it. You would simply replace the pivot values expression with
(SELECT STRING_AGG(DISTINCT CAST(offset AS STRING)) FROM long_format)
But doing this in the example above won't work, because long_format is a Common Table Expression that is only defined inside the EXECUTE IMMEDIATE block. The statement in that block won't be executed until after building it, so at build-time long_format has yet to be defined.
Yet all is not lost. This will work just fine:
SELECT *
FROM d.long_format PIVOT(
ANY_VALUE(vals) AS vals
FOR offset IN ("""
|| (SELECT STRING_AGG(DISTINCT CAST(offset AS STRING)) FROM d.long_format)
|| """
)
)
... provided you first define a BigQuery VIEW (for example) called long_format (or, better, some more expressive name) in a dataset d. That way, both the job that builds the query and the job that runs it will have access to the values.
If successful, you should see both jobs execute and succeed. You should then click 'VIEW RESULTS' on the job that ran the query.
As a final aside, this assumes you are working from the BigQuery console. If you're instead working from a scripting language, that gives you plenty of options to either load and manipulate the data, or build the query in your scripting language rather than massaging BigQuery into doing it for you.
Consider below approach
execute immediate ( select '''
select * except(id) from (
select to_json_string(A) id, * except(A)
from your_table, unnest(A) value with offset
)
pivot (any_value(value) index for offset in ('''
|| (select string_agg('' || val order by offset) from unnest(generate_array(0,999)) val with offset) || '))'
)
If to apply to dummy data like below (with 10 instead of 1000 elements)
select [10,11,12,13,14,15,16,17,18,19] as A union all
select [20,21,22,23,24,25,26,27,28,29] as A union all
select [30,31,32,33,34,35,36,37,38,39] as A
the output is

Inclusion of nulls with ANY_VALUE in BigQuery

I have a 'vendors' table that looks like this...
**company itemKey itemPriceA itemPriceB**
companyA, 203913, 20, 10
companyA, 203914, 20, 20
companyA, 203915, 25, 5
companyA, 203916, 10, 10
It has potentially millions of rows per company and I want to query it to bring back a representative delta between itemPriceA and itemPriceB for each company. I don't care which delta I bring back as long as it isn't zero/null (like row 2 or 4), so I was using ANY_VALUE like this...
SELECT company
, ANY_VALUE(CASE WHEN (itemPriceA-itemPriceB)=0 THEN null ELSE (itemPriceA-itemPriceB) END)
FROM vendors
GROUP BY 1
It seems to be working but I notice 2 sentences that seem contradictory from Google's documentation...
"Returns NULL when expression is NULL for all rows in the group. ANY_VALUE behaves as if RESPECT NULLS is specified; rows for which expression is NULL are considered and may be selected."
If ANY_VALUE returns null "when expression is NULL for all rows in the group" it should NEVER return null for companyA right (since only 2 of 4 rows are null)? But the second sentence sounds like it will indeed include the null rows.
P.s. you may be wondering why I don't simply add a WHERE clause saying "WHERE itemPriceA-itemPriceB>0" but in the event that a company has ONLY matching prices, I still want the company to be returned in my results.
Clarification
I'm afraid the accepted answer will have to show stronger evidence that contradicts the docs.
#Raul Saucedo suggests that the following BigQuery documentation is referring to WHERE clauses:
rows for which expression is NULL are considered and may be selected
This is not the case. WHERE clauses are not mentioned anywhere in the ANY_VALUE docs. (Nowhere on the page. Try to ctrl+f for it.) And the docs are clear, as I'll explain.
#d3wannabe is correct to wonder about this:
It seems to be working but I notice 2 sentences that seem contradictory from Google's documentation...
"Returns NULL when expression is NULL for all rows in the group. ANY_VALUE behaves as if RESPECT NULLS is specified; rows for which expression is NULL are considered and may be selected."
But the docs are not contradictory. The 2 sentences coexist.
"Returns NULL when expression is NULL for all rows in the group." So if all rows in a column are NULL, it will return NULL.
"ANY_VALUE behaves as if RESPECT NULLS is specified; rows for which expression is NULL are considered and may be selected." So if the column has rows mixed with NULLs and actual data, it will select anything from that column, including nulls.
How to create an ANY_VALUE without nulls in BigQuery
We can use ARRAY_AGG to turn a group of values into a list. This aggregate function has the option to INGORE NULLS. We then select 1 item from the list after ignoring nulls.
If we have a table with 2 columns: id and mixed_data, where mixed_data has some rows with nulls:
SELECT
id,
ARRAY_AGG( -- turn the mixed_data values into a list
mixed_data -- we'll create an array of values from our mixed_data column
IGNORE NULLS -- there we go!
LIMIT 1 -- only fill the array with 1 thing
)[SAFE_OFFSET(0)] -- grab the first item in the array
AS any_mixed_data_without_nulls
FROM your_table
GROUP BY id
See similar answers here:
https://stackoverflow.com/a/53508606/6305196
https://stackoverflow.com/a/62089838/6305196
Update, 2022-08-12
There is evidence that the docs may be inconsistent with the actual behavior of the function. See Samuel's latest answer to explore his methodology.
However, we cannot know if the docs are incorrect and ANY_VALUE behaves as expected or if ANY_VALUE has a bug and the docs express the intended behavior. We don't know if Google will correct the docs or the function when they address this issue.
Therefore I would continue to use ARRAY_AGG to create a safe ANY_VALUE that ignores nulls until we see a fix from Google.
Please upvote the issue in Google's Issue Tracker to see this resolved.
This is an explanation about how “any_value works with null values”.
With any_value always return the first value, if there is a value different from null.
SELECT ANY_VALUE(fruit) as any_value
FROM UNNEST([null, "banana",null,null]) as fruit;
Return null if all rows have null values. Refers at this sentence
“Returns NULL when expression is NULL for all rows in the group”
SELECT ANY_VALUE(fruit) as any_value
FROM UNNEST([null, null, null]) as fruit
Return null if one value is null and you specified in the where clause. Refers to these sentences
“ANY_VALUE behaves as if RESPECT NULLS is specified; rows for which
expression is NULL are considered and may be selected.”
SELECT ANY_VALUE(fruit) as any_value
FROM UNNEST(["apple", "banana", null]) as fruit
where fruit is null
Always depends which filter you are using and the field inside the any_value.
You can see this example, return two rows that are different from 0.
SELECT ANY_VALUE(e).company, (itemPriceA-itemPriceB) as value
FROM `vendor` e
where (itemPriceA-itemPriceB)!=0
group by e.company
The documentation says that "NULL are considered and may be" returned by an any_value statement. However, I am quite sure the documentation is wrong here. In the current implementation, which was tested on 13th August 2022, the any_value will return the first value of that column. However, if the table does not have an order by specified, the sorting may be random due to processing of the data on several nodes.
For testing a large table of nulls is needed. To generate_array will come handy for that. This array will have several entries and the value zero for null. The first 1 million entries with value zero are generated in the table tmp. Then table tbl adds before and after the [-100,0,-90,-80,3,4,5,6,7,8,9] the 1 million zeros. Finally, calculating NULLIF(x,0) AS x replaces all zeros by null.
Several test of any_value using the test table tbl are done. If the table is not further sorted, the first value of that column is returned: -100.
WITH
tmp AS (SELECT ARRAY_AGG(0) AS tmp0 FROM UNNEST(GENERATE_ARRAY(1,1000*1000))),
tbl AS (
SELECT
NULLIF(x,0) AS x,
IF(x!=0,x,NULL) AS y,
rand() AS rand
FROM
tmp,
UNNEST(ARRAY_CONCAT(tmp0, [0,0,0,0,0,-100,0,-90,-80,3,4,5,6,7,8,9] , tmp0)) AS x )
SELECT "count rows", COUNT(1) FROM tbl
UNION ALL SELECT "count items not null", COUNT(x) FROM tbl
UNION ALL SELECT "any_value(x): (returns first non null element in list: -100)", ANY_VALUE(x) FROM tbl
UNION ALL SELECT "2nd run", ANY_VALUE(x) FROM tbl
UNION ALL SELECT "3rd run", ANY_VALUE(x) FROM tbl
UNION ALL SELECT "any_value(y)", ANY_VALUE(y) FROM tbl
UNION ALL SELECT "order asc", ANY_VALUE(x) FROM (Select * from tbl order by x asc)
UNION ALL SELECT "order desc (returns largest element: 9)", ANY_VALUE(x) FROM (Select * from tbl order by x desc)
UNION ALL SELECT "order desc", ANY_VALUE(x) FROM (Select * from tbl order by x desc)
UNION ALL SELECT "order abs(x) desc", ANY_VALUE(x) FROM (Select * from tbl order by abs(x) desc )
UNION ALL SELECT "order abs(x) asc (smallest number: 3)", ANY_VALUE(x) FROM (Select * from tbl order by abs(x) asc )
UNION ALL SELECT "order rand asc", ANY_VALUE(x) FROM (Select * from tbl order by rand asc )
UNION ALL SELECT "order rand desc", ANY_VALUE(x) FROM (Select * from tbl order by rand desc )
This gives following result:
The first not null entry, -100 is returned.
Sorting the table by this column causes the any_value to always return the first entry
In the last two examples, the table is ordered by random values, thus any_value returns random entries
If the dataset is larger than 2 million rows, the table may be internally split to be processed; this will result in a not ordered table. Without the order by command the first entry on the table and thus the result of any_value cannot be predicted.
For testing this, please replace the 10th line by
UNNEST(ARRAY_CONCAT(tmp0,tmp0,tmp0,tmp0,tmp0,tmp0,tmp0,tmp0, [0,0,0,0,0,-100,0,-90,-80,3,4,5,6,7,8,9] , tmp0,tmp0)) AS x )

Pairwise array sum aggregate function?

I have a table with arrays as one column, and I want to sum the array elements together:
> create table regres(a int[] not null);
> insert into regres values ('{1,2,3}'), ('{9, 12, 13}');
> select * from regres;
a
-----------
{1,2,3}
{9,12,13}
I want the result to be:
{10, 14, 16}
that is: {1 + 9, 2 + 12, 3 + 13}.
Does such a function already exist somewhere? The intagg extension looked like a good candidate, but such a function does not already exist.
The arrays are expected to be between 24 and 31 elements in length, all elements are NOT NULL, and the arrays themselves will also always be NOT NULL. All elements are basic int. There will be more than two rows per aggregate. All arrays will have the same number of elements, in a query. Different queries will have different number of elements.
My implementation target is: PostgreSQL 9.1.13
General solutions for any number of arrays with any number of elements. Individual elements or the the whole array can be NULL, too:
Simpler in 9.4+ using WITH ORDINALITY
SELECT ARRAY (
SELECT sum(elem)
FROM tbl t
, unnest(t.arr) WITH ORDINALITY x(elem, rn)
GROUP BY rn
ORDER BY rn
);
See:
PostgreSQL unnest() with element number
Postgres 9.3+
This makes use of an implicit LATERAL JOIN
SELECT ARRAY (
SELECT sum(arr[rn])
FROM tbl t
, generate_subscripts(t.arr, 1) AS rn
GROUP BY rn
ORDER BY rn
);
See:
What is the difference between LATERAL JOIN and a subquery in PostgreSQL?
Postgres 9.1
SELECT ARRAY (
SELECT sum(arr[rn])
FROM (
SELECT arr, generate_subscripts(arr, 1) AS rn
FROM tbl t
) sub
GROUP BY rn
ORDER BY rn
);
The same works in later versions, but set-returning functions in the SELECT list are not standard SQL and were frowned upon by some. Should be OK since Postgres 10, though. See:
What is the expected behaviour for multiple set-returning functions in SELECT clause?
db<>fiddle here
Old sqlfiddle
Related:
Is there something like a zip() function in PostgreSQL that combines two arrays?
If you need better performances and can install Postgres extensions, the agg_for_vecs C extension provides a vec_to_sum function that should meet your need. It also offers various aggregate functions like min, max, avg, and var_samp that operate on arrays instead of scalars.
I know the original question and answer are pretty old, but for others who find this... The most elegant and flexible solution I've found is to create a custom aggregate function. Erwin's answer presents some great simple solutions if you only need the single resulting array, but doesn't translate to a solution that could include other table columns and aggregations, in a GROUP BY for example.
With a custom array_add function and array_sum aggregate function:
CREATE OR REPLACE FUNCTION array_add(_a numeric[], _b numeric[])
RETURNS numeric[]
AS
$$
BEGIN
RETURN ARRAY(
SELECT coalesce(a, 0) + coalesce(b, 0)
FROM unnest(_a, _b) WITH ORDINALITY AS x(a, b, n)
ORDER BY n
);
END
$$ LANGUAGE plpgsql;
CREATE AGGREGATE array_sum(numeric[])
(
sfunc = array_add,
stype = numeric[],
initcond = '{}'
);
Then (using the names from your example):
SELECT array_sum(a) a_sums
FROM regres;
Returns your array of sums, and it can just as well be used anywhere other aggregate functions could be used, so if your table also had a column name you wanted to group by, and another array of numbers, column b:
SELECT name, array_sum(a) a_sums, array_sum(b) b_sums
FROM regres
GROUP BY name;
You won't get quite the performance you'd get out of the built-in sum function and just selecting sum(a[1]), sum(a[2]), sum(a[3]), you'd have to implement the array_add function as a compiled C function to get that. But in cases where you don't have the ability to add custom C functions (like a managed cloud database, e.g. AWS RDS), or you're not aggregating huge numbers of rows, the difference probably won't be noticed.

Calling table valued function twice. Could be once?

I need to use in SQL a function which returns a table
At this moment I have:
SELECT
K.ID,
(SELECT A from dbo.TableFunction1 (K.ID,0,77)) AS A,
(SELECT B from dbo.TableFunction1 (K.ID,0,77)) AS B
FROM K
I'm worried because I execute the same function with the same parameters twice, once to get one column and next time to get another column.
It turns out I can't do:
SELECT
K.ID,
(SELECT A,B from dbo.TableFunction1 (K.ID,0,77))
FROM K
as I get: Only one expression can be specified in the select list when the subquery is not introduced with EXISTS.
Could this query be improved so I called the function only once?
Try using cross apply:
select K.ID, tf1.A, tf1.B
from K cross apply
dbo.TableFunction1(K.ID, 0, 77) tf1
You can do 3 things here:
Use cross apply
select k.id, f.b, f.b
from k
cross apply dbo.TableFunction(k.id, 0, 77)
This will work fine if your query stays that simple, but if you start to have other joins, that limit the number of rows that you would return from "K", then you can still end up running "TableFunction" on every row in "K". I've seen that turn into a performance nightmare.
Convert the function to a 2 scalar functions
select
K.ID,
dbo.ScalarFunctionA (K.ID,0,77)) AS A,
dbo.ScalarFunctionB (K.ID,0,77)) AS B
FROM K
This also has drawbacks if you have a big query within that function, you're now running that query twice for every row you return. If you're only returning 1 row, no problem, if you're returning thousands performance takes another hit.
Unwrap the function completely and include it within the query. Most likely the fastest, but comes with the drawback of not reusing the code.

Purposely having a query return blank entries at regular intervals

I want to write a query that returns 3 results followed by blank results followed by the next 3 results, and so on. So if my database had this data:
CREATE TABLE table (a integer, b integer, c integer, d integer);
INSERT INTO table (a,b,c,d)
VALUES (1,2,3,4),
(5,6,7,8),
(9,10,11,12),
(13,14,15,16),
(17,18,19,20),
(21,22,23,24),
(25,26,37,28);
I would want my query to return this
1,2,3,4
5,6,7,8
9,10,11,12
, , ,
13,14,15,16
17,18,19,20
21,22,23,24
, , ,
25,26,27,28
I need this to work for arbitrarily many entries that I select for, have three be grouped together like this.
I'm running postgresql 8.3
This should work flawlessly in PostgreSQL 8.3
SELECT a, b, c, d
FROM (
SELECT rn, 0 AS rk, (x[rn]).*
FROM (
SELECT x, generate_series(1, array_upper(x, 1)) AS rn
FROM (SELECT ARRAY(SELECT tbl FROM tbl) AS x) x
) y
UNION ALL
SELECT generate_series(3, (SELECT count(*) FROM tbl), 3), 1, (NULL::tbl).*
ORDER BY rn, rk
) z
Major points
Works for a query that selects all columns of tbl.
Works for any table.
For selecting arbitrary columns you have to substitute (NULL::tbl).* with a matching number of NULL columns in the second query.
Assuming that NULL values are ok for "blank" rows.
If not, you'll have to cast your columns to text in the first and substitute '' for NULL in the second SELECT.
Query will be slow with very big tables.
If I had to do it, I would write a plpgsql function that loops through the results and inserts the blank rows. But you mentioned you had no direct access to the db ...
In short, no, there's not an easy way to do this, and generally, you shouldn't try. The database is concerned with what your data actually is, not how it's going to be displayed. It's not an appropriate scope of responsibility to expect your database to return "dummy" or "extra" data so that some down-stream process produces a desired output. The generating script needs to do that.
As you can't change your down-stream process, you could (read that with a significant degree of skepticism and disdain) add things like this:
Select Top 3
a, b, c, d
From
table
Union Select Top 1
'', '', '', ''
From
table
Union Select Top 3 Skip 3
a, b, c, d
From
table
Please, don't actually try do that.
You can do it (at least on DB2 - there doesn't appear to be equivalent functionality for your version of PostgreSQL).
No looping needed, although there is a bit of trickery involved...
Please note that though this works, it's really best to change your display code.
Statement requires CTEs (although that can be re-written to use other table references), and OLAP functions (I guess you could re-write it to count() previous rows in a subquery, but...).
WITH dataList (rowNum, dataColumn) as (SELECT CAST(CAST(:interval as REAL) /
(:interval - 1) * ROW_NUMBER() OVER(ORDER BY dataColumn) as INTEGER),
dataColumn
FROM dataTable),
blankIncluder(rowNum, dataColumn) as (SELECT rowNum, dataColumn
FROM dataList
UNION ALL
SELECT rowNum - 1, :blankDataColumn
FROM dataList
WHERE MOD(rowNum - 1, :interval) = 0
AND rowNum > :interval)
SELECT *
FROM dataList
ORDER BY rowNum
This will generate a list of those elements from the datatable, with a 'blank' line every interval lines, as ordered by the initial query. The result set only has 'blank' lines between existing lines - there are no 'blank' lines on the ends.