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
I am looking for a way to check if a string contains any words in another field which is a single string that holds a list of items. Something like this...
id items (STRING)
1 burger;hotdog
I have a second dataset that might look like...
transaction_id description amount
10 cheeseburger 10
Now I need to grab the amount if the description matches any items in the first table, in this case it does match with the string burger, however, i can't seem to get the SQL right since if I were to use LIKE ANY in Snowflake, i'd need to pass in **('%burger%",'%hotdog%') which are two separate strings - in this case I can't make explicit calls as each id/item permutation may be different in the first table. While in Redshift when I try to use
CASE WHEN lower(t.description) SIMILAR TO '%(' || replace(items,';','|') || ')%' then amount END
I get the following error: Specified types or functions (one per INFO message) not supported on Redshift tables.
Thanks in advance!
If your wanting a snowflake answer:
WITH keys AS (
SELECT * FROM VALUES (1,'burger;hotdog') a(id,items)
), data AS (
SELECT * FROM VALUES (10,'cheeseburger',10) b(transaction_id, description, amount)
), seq_keys AS (
SELECT s.seq_id, f.value as key
FROM (
SELECT seq8() as seq_id, k.*
FROM keys AS k
) AS s
,lateral flatten(input=>split(s.items,';')) F
)
SELECT d.*, sk.*
FORM data d
JOIN seq_keys sk ON d.description ILIKE '%'||sk.key||'%'
gives:
TRANSACTION_ID DESCRIPTION AMOUNT SEQ_ID KEY
10 cheeseburger 10 0 "burger"
which is you distinct on the SEQ_ID then you can de-dupe if there are multi keys that match.. I would be inclined to also add an ID to the "data table".
I am trying to pull records whose arrays only meet a certain condition.
For example, I want only the results that contain "IAB3".
Here is what the table looks like
Table Name:
bids
Column Names:
BidderBanner / WinCat
Entries:
1600402 / null
1911048 / null
1893069 / [IAB3-11, IAB3]
1214894 / IAB3
How I initially thought it would be
SELECT * FROM bids WHERE WinCat = "IAB3"
but I get an error that says no match for operator types array, string.
The database is in Google Big Query.
Below is for BigQuery Standard SQL
#standardSQL
SELECT * FROM `project.dataset.bids` WHERE 'IAB3' IN UNNEST(WinCat)
You can test, play with above using sample data from your question as in example below
#standardSQL
WITH `project.dataset.bids` AS (
SELECT 1600402 BidderBanner, NULL WinCat UNION ALL
SELECT 1911048, NULL UNION ALL
SELECT 1893069, ['IAB3-11', 'IAB3'] UNION ALL
SELECT 1214894, ['IAB3']
)
SELECT * FROM `project.dataset.bids` WHERE 'IAB3' IN UNNEST(WinCat)
with result
you need to use single quotes in sql for all strings. it should be WHERE WinCat = 'IAB3' not WHERE WinCat = "IAB3"
One method uses unnest(), something like this:
SELECT b.*
FROM bids b
WHERE 'IAB3' IN (SELECT unnest(b.WinCats))
However, array syntax varies among the databases that support them and they are no part of "standard SQL".
this will work:
SELECT * FROM bids WHERE REGEXP_LIKE (WinCat, '(.)*(IAB3)+()*');
Hello i am trying to get my queries log cost, i get the total amount but when i try to break it down per dataset i get this error:
' Cannot access field datasetId on a value with type ARRAY> at '
this is my query i am trying to run:
WITH
data AS (
SELECT
protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent AS jobCompletedEvent,
(
SELECT
ARRAY_TO_STRING((
SELECT
ARRAY_AGG(datasetId)
FROM
UNNEST(protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent.job.jobStatistics.referencedTables.datasetId) ))) AS datasetIds
FROM
`kkk111.bq_audit_log_export.cloudaudit_googleapis_com_data_access_20190206` )
SELECT
datasetIds,
FORMAT('%9.2f',5.0 * (SUM(jobCompletedEvent.job.jobStatistics.totalBilledBytes)/POWER(2, 40))) AS Estimated_USD_Cost
FROM
data
WHERE
jobCompletedEvent.eventName = 'query_job_completed'
GROUP BY
datasetIds
ORDER BY
Estimated_USD_Cost DESC
I am using Standard SQL Dialect
how do i cast this field:
protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent.job.jobStatistics.referencedTables.datasetId
from array to a string ?
what am i missing ?
Thanks.
Below is for BigQuery Standard SQL
#standardSQL
WITH data AS (
SELECT
protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent AS jobCompletedEvent,
ref.datasetId AS datasetId
FROM `kkk111.bq_audit_log_export.cloudaudit_googleapis_com_data_access_20190206`,
UNNEST(protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent.job.jobStatistics.referencedTables) ref
)
SELECT
datasetId,
FORMAT('%9.2f',5.0 * (SUM(jobCompletedEvent.job.jobStatistics.totalBilledBytes)/POWER(2, 40))) AS Estimated_USD_Cost
FROM data
WHERE jobCompletedEvent.eventName = 'query_job_completed'
GROUP BY datasetId
ORDER BY Estimated_USD_Cost DESC
As you can see there, obviously you need to UNNEST referencedTables ARRAY but also you need to make sure your final calculation of Cost is as close to correct one as possible. The same query can reference multiple tables from the same dataset, so you better have DISTINCT in your CTE. But also, same query can reference tables from multiple datasets - so in this same billing bytes will be attributed to multiple datasets, so you will have overestimation! I don't know your exact intent - but you might want to introduce some logic to distribute the cost among the referenced datasets.
You need to UNNEST the outer array in order to select the dataset ID inside:
SELECT
ARRAY_TO_STRING((
SELECT ARRAY_AGG(datasetId)
FROM UNNEST(protopayload_auditlog.servicedata_v1_bigquery.jobCompletedEvent.job.jobStatistics.referencedTables)
), ',') AS datasetIds
FROM ...
For example ,
I use the following function to convert rows into json in PostgreSQL 9.2
select row_to_json(row(productid, product)) from gtab04;
and this will returns below results
row_to_json
---------------
{"f1":3029,"f2":"DIBIZIDE M TAB"}
{"f1":3026,"f2":"MELMET 1000 SR TAB"}
{"f1":2715,"f2":"GLUCORED FORTE"}
{"f1":3377,"f2":"AZINDICA 500 TAB"}
unfortunately it loses the field names and replaces them with f1, f2, f3, etc.
How can I get the actual field names or cast field name?
To work around this we must either create a row type and cast the row to that type or use a subquery. A subquery will typically be easier.
select row_to_json(t)
from (
select productid, product from gtab04
) t
If one wants to prevent a sub-query, json_build_object() might be a solution. It does not map the column name, but let's your set the JSON keys explicitly.
Query
SELECT json_build_object('productid', productid, 'product', product) FROM gtab04;
json_build_object
------------------
{"productid":3029,"product":"DIBIZIDE M TAB"}
{"productid":3026,"product":"MELMET 1000 SR TAB"}
{"productid":2715,"product":"GLUCORED FORTE"}
{"productid":3377,"product":"AZINDICA 500 TAB"}
View on DB Fiddle