I have a table A within a dataset in Bigquery. This table has multiple columns and one of the columns called hits_eventInfo_eventLabel has values like below:
{ID:AEEMEO,Score:8.990000;ID:SEAMCV,Score:8.990000;ID:HBLION;Property
ID:DNSEAWH,Score:0.391670;ID:CP1853;ID:HI2367;ID:H25600;}
If you write this string out in a tabular form, it contains the following data:
**ID | Score**
AEEMEO | 8.990000
SEAMCV | 8.990000
HBLION | -
DNSEAWH | 0.391670
CP1853 | -
HI2367 | -
H25600 | -
Some IDs have scores, some don't. I have multiple records with similar strings populated under the column hits_eventInfo_eventLabel within the table.
My question is how can I parse this string successfully WITHIN BIGQUERY so that I can get a list of property ids and their respective recommendation scores (if existing)? I would like to have the order in which the IDs appear in the string to be preserved after parsing this data.
Would really appreciate any info on this. Thanks in advance!
I would use combination of SPLIT to separate into different rows and REGEXP_EXTRACT to separate into different columns, i.e.
select
regexp_extract(x, r'ID:([^,]*)') as id,
regexp_extract(x, r'Score:([\d\.]*)') score from (
select split(x, ';') x from (
select 'ID:AEEMEO,Score:8.990000;ID:SEAMCV,Score:8.990000;ID:HBLION;Property ID:DNSEAWH,Score:0.391670;ID:CP1853;ID:HI2367;ID:H25600;' as x))
It produces the following result:
Row id score
1 AEEMEO 8.990000
2 SEAMCV 8.990000
3 HBLION null
4 DNSEAWH 0.391670
5 CP1853 null
6 HI2367 null
7 H25600 null
You can write your own JavaScript functions in BigQuery to get exactly what you want now: http://googledevelopers.blogspot.com/2015/08/breaking-sql-barrier-google-bigquery.html
Related
I've got an issue when trying to visualize in Google Data Studio some information from a denormalized table.
Context: I want to gather all the contact of a company and there related orders in a table in Big Query. Contacts can have no order or multiple orders. Following Big Query best practice, this table is denormalized and all the orders for a client are in arrays of struct. It looks like this:
Fields Examples:
+-------+------------+-------------+-----------+
| Row # | Contact_Id | Orders.date | Orders.id |
+-------+------------+-------------+-----------+
|- 1 | 23 | 2019-02-05 | CB1 |
| | | 2020-03-02 | CB293 |
|- 2 | 2321 | - | - |
|- 3 | 77 | 2010-09-03 | AX3 |
+-------+------------+-------------+-----------+
The issue is when I want to use this table as a data source in Data Studio.
For instance, if I build a table with Contact_Id as dimension, everything is fine and I can see all my contacts. However, if I add any dimensions from the Orders struct, all info from contact with no orders are not displayed. For instance, all info from Contact_Id 2321 is removed from the table.
Have you find any workaround to visualize these empty arrays (for instance as null values)?
The only solution I've found is to build an intermediary table with the orders unnested.
The way I've just discovered to work around this is to add an extra field in my DS-> BQ connector:
ARRAY_LENGTH(fields.orders) AS numberoforders
This will return zero if the array is empty - you can then create calculated fields within DataStudio - using the "numberoforders" field to force values to NULL or zero.
You can fix this behaviour by changing a little your query on the BigQuery connector.
Instead of doing this:
SELECT
Contact_id,
Orders
FROM myproject.mydataset.mytable
try this:
SELECT
Contact_id,
IF(ARRAY_LENGTH(Orders) > 0, Orders, [STRUCT(CAST(NULL AS DATE) AS date, CAST(NULL AS STRING) AS id)]) AS Orders
FROM myproject.mydataset.mytable
This way you are forcing your repeated field to have, at least, an array containing NULL values and hence Data Studio will represent those missing values.
Also, if you want to create new calculated fields using one of the nested fields, you should check before if the value is NULL to avoid filling all NULL values. For example, if you have a repeated and nested field which can be 1 or 0, and you want to create a calculated field swaping the value, you should do:
IF(myfield.key IS NOT NULL, IF(myfield.key = 1, 0, 1), NULL)
Here you can see what happens if you check before swaping and if you don't:
Original value No check Check
1 0 0
0 1 1
NULL 1 NULL
1 0 0
NULL 1 NULL
I have a table like this:
I want to perform count on different set of columns (all subsets where there is at least one element from X and one element from Y). How can I do that in Postgres?
For example, I may have {x1,x2,y3}, {x4,y1,y2,y3},etc. I want to count number of "id"s having 1 in each set. So for the first set:
SELECT COUNT(id) FROM table WHERE x1=1 AND x2=1 AND x3=1;
and for the second set does the same:
SELECT COUNT(id) FROM table WHERE x4=1 AND y1=1 AND y2=1 AND y3=1;
Is it possible to write a loop that goes over all these sets and query the table accordingly? The array will have more than 10000 sets, so it cannot be done manually.
You should be able convert the table columns to an array using ARRAY[col1, col2,...], then use the array_positions function, setting the second parameter to be the value you're checking for. So, given your example above, this query:
SELECT id, array_positions(array[x1,x2,x3,x4,y1,y2,y3,y4], 1)
FROM tbl
ORDER BY id;
Will yield this result:
+----+-------------------+
| id | array_positions |
+----+-------------------+
| a | {1,4,5} |
| b | {1,2,4,7} |
| c | {1,2,3,4,6,7,8} |
+----+-------------------+
Here's a SQL Fiddle.
I already have the code to display the highest aggregate value for a ID.
select max(fk3_job_role_id),max(sum(no_of_placements))
from fact_accounts
group by fk3_job_role_id
the result looks like:
[max(fk3_job_role_id)] | [max(sum(no_of_placements))]
-----------------------|-----------------------------
5 | 25
However, i want to display the job_role_desc instead of fk3_job_role_id represented by the same id.
The table for it looks like:
[job_role_id] | [job_role_desc]
--------------------------------
1 | job1
2 | job2
3 | job3
4 | job4
5 | job5
select job_role_desc,T.total_sum from fact_accounts where job_role_id in (select max(fk3_job_role_id),max(sum(no_of_placements)) as total_sum from fact_accounts group by fk3_job_role_id) T
You need to query for the job description by using a subquery. The above query first fetches the data according to the query inside the brackets( also known popularly as a subquery ). The result returned from this query is used to compare with all the other id's in the main table by a simple "in" clause.
Edit
If you also need the sum of placements you can get it by using a reference to the table created during the execution of the subquery
I need to pull the record containing the highest value, specifically I only need the value from that field. The problem is that the column is nvarchar format that contains a mix of numbers and special characters. The following is just an example:
PK | Column 2 (nvarchar)
-------------------
1 | .1.1.
2 | .10.1.1
3 | .5.1.7
4 | .4.1.
9 | .10.1.2
15 | .5.1.4
Basically, because of natural sort, the items in column 2 are sorted as strings. So instead of returning the PK for the row containing ".10.1.2" as the highest value i get the PK for the row that contains ".5.1.7" instead.
I attempted to write some functions to do this but it seems what I've written looked way more complicated than it should be. Anyone got something simple or complicated functions are the only way?
I want to make clear that I'm trying to grab the PK of the record that contains the highest Column 2 value.
This query might return what you desire
SELECT MAX(CAST(REPLACE(Column2, '.', '') as INT)) FROM table
Let's say I had a table full of records that I wanted to pull random records from. However, I want certain rows in that table to appear more often than others (and which ones vary by user). What's the best way to go about this, using SQL?
The only way I can think of is to create a temporary table, fill it with the rows I want to be more common, and then pad it with other randomly selected rows from the table. Is there a better way?
One way I can think of is to create another column in the table which is a rolling sum of your weights, then pull your records by generating a random number between 0 and the total of all your weights, and pull the row with the highest rolling sum value less than the random number.
For example, if you had four rows with the following weights:
+---+--------+------------+
|row| weight | rollingsum |
+---+--------+------------+
| a | 3 | 3 |
| b | 3 | 6 |
| c | 4 | 10 |
| d | 1 | 11 |
+---+--------+------------+
Then, choose a random number n between 0 and 11, inclusive, and return row a if 0<=n<3, b if 3<=n<6, and so on.
Here are some links on generating rolling sums:
http://dev.mysql.com/tech-resources/articles/rolling_sums_in_mysql.html
http://dev.mysql.com/tech-resources/articles/rolling_sums_in_mysql_followup.html
I don't know that it can be done very easily with SQL alone. With T-SQL or similar, you could write a loop to duplicate rows, or you can use the SQL to generate the instructions for doing the row duplication instead.
I don't know your probability model, but you could use an approach like this to achieve the latter. Given these table definitions:
RowSource
---------
RowID
UserRowProbability
------------------
UserId
RowId
FrequencyMultiplier
You could write a query like this (SQL Server specific):
SELECT TOP 100 rs.RowId, urp.FrequencyMultiplier
FROM RowSource rs
LEFT JOIN UserRowProbability urp ON rs.RowId = urp.RowId
ORDER BY ISNULL(urp.FrequencyMultiplier, 1) DESC, NEWID()
This would take care of selecting a random set of rows as well as how many should be repeated. Then, in your application logic, you could do the row duplication and shuffle the results.
Start with 3 tables users, data and user-data. User-data contains which rows should be prefered for each user.
Then create one view based on the data rows that are prefered by the the user.
Create a second view that has the none prefered data.
Create a third view which is a union of the first 2. The union should select more rows from the prefered data.
Then finally select random rows from the third view.