@Jayesh Potwade - Thanks for the question and using MS Q&A platform.
Yes, dynamic SQL queries are supported on Azure Databricks SQL cluster. You can use the spark-sql
command to execute dynamic SQL queries on Azure Databricks SQL cluster. Here is an example:
%sql SELECT * FROM my_table WHERE column_name = '${value}'
In this example, ${value}
is a parameter that can be passed dynamically to the query. You can also use the spark.sql()
function to execute dynamic SQL queries in Python or Scala. Here is an example:
from pyspark.sql.functions import lit
value = "some_value"
query = "SELECT * FROM my_table WHERE column_name = '{}'".format(value)
df = spark.sql(query)
In this example, value
is a parameter that can be passed dynamically to the query. The spark.sql()
function is used to execute the query and return the result as a DataFrame.
You can use the EXECUTE IMMEDIATE
statement to execute dynamic SQL queries in Databricks SQL. Here is an example:
DECLARE @query NVARCHAR(MAX)
SET @query = 'SELECT * FROM my_table WHERE column_name = ''' + @value + ''''
EXECUTE IMMEDIATE @query
In this example, @value
is a parameter that can be passed dynamically to the query. The EXECUTE IMMEDIATE
statement is used to execute the query.
Regarding your requirement for aggregated users, you can use a CASE
statement to check if the selected columns have a value greater than 10. Here is an example:
SELECT
Gender,
Age_Group,
SUM(CASE WHEN Value > 10 THEN Value ELSE 0 END) AS Aggregate_Value
FROM
my_table
GROUP BY
Gender,
Age_Group
In this example, the SUM
function is used to calculate the aggregate value for each group. The CASE
statement is used to check if the Value
column is greater than 10. If it is, then the Value
is included in the sum. Otherwise, 0 is included in the sum.
You can modify this query to include only the selected columns by the user. You can also modify the CASE
statement to check if the selected columns have a value greater than 10.
Hope this helps. Do let us know if you any further queries.