I have a dataset containing a column in json with an attribute giving me a list, and I would like to unnest it to join some different data.
I thought about json_extract_scalar the json_data, then I could split it and finally unnest with other operations, however I got a problem.
In my case, when i run the json_extract it works fine but i cannot convert to a varchar. In the other hand, if i use json_extract_scalar it returns a null value.
I think the problem should be the quotation marks, but I am not sure how to deal with it - and even if this is the correct problem.
Let me give you a sample of the data:
{"my_test_list":["756596263-0","743349523-371296","756112380-0","755061590-0"]}
Can you guys give me some advice?
I'm querying SQL in Presto.
What you are storing under key my_test_list is a JSON array, not a scalar value - which is why json_extract_scalar() returns null.
It is rather unclear how you want to use that data. A typical solution is to cast it to an array, that you can then use as needed, for example by unnesting it. The base syntax would be:
cast(json_extract(mycol, '$.my_test_list') as array(varchar))
You would then use that in a lateral join, like:
select t.mycol, x.myval
from mytable t
cross join unnest(
cast(json_extract(mycol, '$.my_test_list') as array(varchar))
) as x(myval)
I would like to convert this table
to something like this
the long string can be dynamic so it's important to me that it's not a fixed solution for these values specifically
Please help, i'm using big query
You could start by using SPLIT SPLIT(value[, delimiter]) to convert your long string into separate key-value pairs in an array.
This will be sensitive to you having commas as part of your values.
SPLIT(session_experiments, ',')
Then you could either FLATTEN that array or access each element, and then use some REGEXs to separate the key and the value.
If you share more context on your restrictions and intended result I could try and put together a query for you that does exactly what you want.
It's not possible what you want, however, there is a better practice for BigQuery.
You can use arrays of structs to store that information in a table.
Let's say you have a table like that
You can use that sample query to understand how to use it.
with rawdata AS
(
SELECT 1 as id, 'test1-val1,test2-val2,test3-val3' as experiments union all
SELECT 1 as id, 'test1-val1,test3-val3,test5-val5' as experiments
)
select
id,
(select array_agg(struct(split(param, '-')[offset(0)] as experiment, split(param, '-')[offset(1)] as value)) from unnest(split(experiments)) as param ) as experiments
from rawdata
The output will look like that:
After having that output, it's more convenient to manipulate the data
I have some json data which includes a property 'characters' and it looks like this:
select json_data['characters'] from latest_snapshot_events
Returns: [{"CHAR_STARS":1,"CHAR_A1_LVL":1,"ITEM_POWER":60,"CHAR_A3_LVL":1,"CHAR_TIER":1,"ITEM":10,"shards":0,"CHAR_TPIECES":0,"CHAR_A5_LVL":0,"CHAR_A2_LVL":1,"CHAR_A4_LVL":1,"ITEM_CATEGORY":"Character","ITEM_LEVEL":3},{"CHAR_STARS":1,"CHAR_A1_LVL":1,"ITEM_POWER":50,"CHAR_A3_LVL":1,"CHAR_TIER":1,"ITEM":39,"shards":0,"CHAR_TPIECES":0,"CHAR_A5_LVL":0,"CHAR_A2_LVL":1,"CHAR_A4_LVL":1,"ITEM_CATEGORY":"Character","ITEM_LEVEL":2},{"CHAR_STARS":1,"CHAR_A1_LVL":1,"ITEM_POWER":80,"CHAR_A3_LVL":1,"CHAR_TIER":1,"ITEM":6801450488388220,"shards":0,"CHAR_TPIECES":0,"CHAR_A5_LVL":1,"CHAR_A2_LVL":1,"CHAR_A4_LVL":1,"ITEM_CATEGORY":"Character","ITEM_LEVEL":4},{"CHAR_STARS":1,"CHAR_A1_LVL":1,"ITEM_POWER":85,"CHAR_A3_LVL":1,"CHAR_TIER":1,"ITEM":8355588830097610,"shards":0,"CHAR_TPIECES":5,"CHAR_A5_LVL":0,"CHAR_A2_LVL":1,"CHAR_A4_LVL":1,"ITEM_CATEGORY":"Character","ITEM_LEVEL":4}]
This is returned on a single row. I would like a single row for each item within the array.
I found several SO posts and other blogs advising me to use unnest(). I've tried this several times and cannot get a result to return. For example, here is the documentation from presto. The bottom covers unnest as a stand in for hive's lateral view explode:
SELECT student, score
FROM tests
CROSS JOIN UNNEST(scores) AS t (score);
So I tried to apply this to my table:
characters as (
select
jdata.characters
from latest_snapshot_events
cross join unnest(json_data) as t(jdata)
)
select * from characters;
where json_data is the field in latest_snapshot_events that contains the the property 'characters' which is an array like the one shown above.
This returns an error:
[Simba]AthenaJDBC An error has been thrown from the AWS Athena client. SYNTAX_ERROR: line 69:12: Column alias list has 1 entries but 't' has 2 columns available
How can I unnest/explode latest_snapshot_events.json_data['characters'] onto multiple rows?
Since characters is a JSON array in textual representation, you'll have to:
Parse the JSON text with json_parse to produce a value of type JSON.
Convert the JSON value into a SQL array using CAST.
Explode the array using UNNEST.
For instance:
WITH data(characters) AS (
VALUES '[{"CHAR_STARS":1,"CHAR_A1_LVL":1,"ITEM_POWER":60,"CHAR_A3_LVL":1,"CHAR_TIER":1,"ITEM":10,"shards":0,"CHAR_TPIECES":0,"CHAR_A5_LVL":0,"CHAR_A2_LVL":1,"CHAR_A4_LVL":1,"ITEM_CATEGORY":"Character","ITEM_LEVEL":3},{"CHAR_STARS":1,"CHAR_A1_LVL":1,"ITEM_POWER":50,"CHAR_A3_LVL":1,"CHAR_TIER":1,"ITEM":39,"shards":0,"CHAR_TPIECES":0,"CHAR_A5_LVL":0,"CHAR_A2_LVL":1,"CHAR_A4_LVL":1,"ITEM_CATEGORY":"Character","ITEM_LEVEL":2},{"CHAR_STARS":1,"CHAR_A1_LVL":1,"ITEM_POWER":80,"CHAR_A3_LVL":1,"CHAR_TIER":1,"ITEM":6801450488388220,"shards":0,"CHAR_TPIECES":0,"CHAR_A5_LVL":1,"CHAR_A2_LVL":1,"CHAR_A4_LVL":1,"ITEM_CATEGORY":"Character","ITEM_LEVEL":4},{"CHAR_STARS":1,"CHAR_A1_LVL":1,"ITEM_POWER":85,"CHAR_A3_LVL":1,"CHAR_TIER":1,"ITEM":8355588830097610,"shards":0,"CHAR_TPIECES":5,"CHAR_A5_LVL":0,"CHAR_A2_LVL":1,"CHAR_A4_LVL":1,"ITEM_CATEGORY":"Character","ITEM_LEVEL":4}]'
)
SELECT entry
FROM data, UNNEST(CAST(json_parse(characters) AS array(json))) t(entry)
which produces:
entry
-----------------------------------------------------------------------
{"CHAR_STARS":1,"CHAR_A1_LVL":1,"ITEM_POWER":60,"CHAR_A3_LVL":1,...
{"CHAR_STARS":1,"CHAR_A1_LVL":1,"ITEM_POWER":50,"CHAR_A3_LVL":1,...
{"CHAR_STARS":1,"CHAR_A1_LVL":1,"ITEM_POWER":80,"CHAR_A3_LVL":1,...
{"CHAR_STARS":1,"CHAR_A1_LVL":1,"ITEM_POWER":85,"CHAR_A3_LVL":1,...
In the example above, I convert the JSON value into an array(json), but
you can further convert it to something more concrete if the values inside each
array entry have a regular schema. For example, for your data, it is
possible to cast it to an array(map(varchar, json)) since every element in the
array is a JSON object.
json_parse works if your initial data is a JSON string. However, for array(row) types (i.e. an array of objects/dictionaries), casting to array(json) will convert each row into an array, removing all keys from the object and preventing you from using dot notation or json_extract functions.
To unnest array(row) data, the syntax is much simpler:
CROSS JOIN UNNEST(my_array) AS my_row
I got stuck with this error trying to unpivot data.
This might help someone:
SELECT a_col, b_col
FROM
(
SELECT MAP(
ARRAY['a', 'b', 'c', 'd'],
ARRAY[1, 2, 3, 4]
) my_col
) CROSS JOIN UNNEST(my_col) as t(a_col, b_col)
t() allows you define multiple columns as outputs.
I have some data in a postgres table that is a string representation of an array of json data, like this:
[
{"UsageInfo"=>"P-1008366", "Role"=>"Abstract", "RetailPrice"=>2, "EffectivePrice"=>0},
{"Role"=>"Text", "ProjectCode"=>"", "PublicationCode"=>"", "RetailPrice"=>2},
{"Role"=>"Abstract", "RetailPrice"=>2, "EffectivePrice"=>0, "ParentItemId"=>"396487"}
]
This is is data in one cell from a single column of similar data in my database.
The datatype of this stored in the db is varchar(max).
My goal is to find the average RetailPrice of EVERY json item with "Role"=>"Abstract", including all of the json elements in the array, and all of the rows in the database.
Something like:
SELECT avg(json_extract_path_text(json_item, 'RetailPrice'))
FROM (
SELECT cast(json_items to varchar[]) as json_item
FROM my_table
WHERE json_extract_path_text(json_item, 'Role') like 'Abstract'
)
Now, obviously this particular query wouldn't work for a few reasons. Postgres doesn't let you directly convert a varchar to a varchar[]. Even after I had an array, this query would do nothing to iterate through the array. There are probably other issues with it too, but I hope it helps to clarify what it is I want to get.
Any advice on how to get the average retail price from all of these arrays of json data in the database?
It does not seem like Redshift would support the json data type per se. At least, I found nothing in the online manual.
But I found a few JSON function in the manual, which should be instrumental:
JSON_ARRAY_LENGTH
JSON_EXTRACT_ARRAY_ELEMENT_TEXT
JSON_EXTRACT_PATH_TEXT
Since generate_series() is not supported, we have to substitute for that ...
SELECT tbl_id
, round(avg((json_extract_path_text(elem, 'RetailPrice'))::numeric), 2) AS avg_retail_price
FROM (
SELECT *, json_extract_array_element_text(json_items, pos) AS elem
FROM (VALUES (0),(1),(2),(3),(4),(5)) a(pos)
CROSS JOIN tbl
) sub
WHERE json_extract_path_text(elem, 'Role') = 'Abstract'
GROUP BY 1;
I substituted with a poor man's solution: A dummy table counting from 0 to n (the VALUES expression). Make sure you count up to the maximum number of possible elements in your array. If you need this on a regular basis create an actual numbers table.
Modern Postgres has much better options, like json_array_elements() to unnest a json array. Compare to your sibling question for Postgres:
Can get an average of values in a json array using postgres?
I tested in Postgres with the related operator ->>, where it works:
SQL Fiddle.
I have a column in our database called min_crew that has varying character arrays such as '{CA, FO, FA}'.
I have a query where I'm trying to get aggregates of these arrays without success:
SELECT use.user_sched_id, array_agg(se.sched_entry_id) AS seids
, array_agg(se.min_crew)
FROM base.sched_entry se
LEFT JOIN base.user_sched_entry use ON se.sched_entry_id = use.sched_entry_id
WHERE se.sched_entry_id = ANY(ARRAY[623, 625])
GROUP BY user_sched_id;
Both 623 and 625 have the same use.user_sched_id, so the result should be the grouping of the seids and the min_crew, but I just keep getting this error:
ERROR: could not find array type for data type character varying[]
If I remove the array_agg(se.min_crew) portion of the code, I do get a table returned with the user_sched_id = 2131 and seids = '{623, 625}'.
The standard aggregate function array_agg() only works for base types, not array types as input.
(But Postgres 9.5+ has a new variant of array_agg() that can!)
You could use the custom aggregate function array_agg_mult() as defined in this related answer:
Selecting data into a Postgres array
Create it once per database. Then your query could work like this:
SELECT use.user_sched_id, array_agg(se.sched_entry_id) AS seids
,array_agg_mult(ARRAY[se.min_crew]) AS min_crew_arr
FROM base.sched_entry se
LEFT JOIN base.user_sched_entry use USING (sched_entry_id)
WHERE se.sched_entry_id = ANY(ARRAY[623, 625])
GROUP BY user_sched_id;
There is a detailed rationale in the linked answer.
Extents have to match
In response to your comment, consider this quote from the manual on array types:
Multidimensional arrays must have matching extents for each dimension.
A mismatch causes an error.
There is no way around that, the array type does not allow such a mismatch in Postgres. You could pad your arrays with NULL values so that all dimensions have matching extents.
But I would rather translate the arrays to a comma-separated lists with array_to_string() for the purpose of this query and use string_agg() to aggregate the text - preferably with a different separator. Using a newline in my example:
SELECT use.user_sched_id, array_agg(se.sched_entry_id) AS seids
,string_agg(array_to_string(se.min_crew, ','), E'\n') AS min_crews
FROM ...
Normalize
You might want to consider normalizing your schema to begin with. Typically, you would implement such an n:m relationship with a separate table like outlined in this example:
How to implement a many-to-many relationship in PostgreSQL?