@ChineduLB  WITH data_counts AS ( SELECT COUNT(*) AS count_table1, COUNT(*) AS count_table2, COUNT(*) AS count_table3, COUNT(*) AS count_table4, COUNT(*) AS count_table5, COUNT(*) AS count_table6 FROM table1 WHERE date_partition = 'your_date' -- Replace 'your_date' with the specific date you're interested in UNION ALL SELECT COUNT(*), COUNT(*), COUNT(*), COUNT(*), COUNT(*), COUNT(*) FROM table2 WHERE date_partition = 'your_date' UNION ALL SELECT COUNT(*), COUNT(*), COUNT(*), COUNT(*), COUNT(*), COUNT(*) FROM table3 WHERE date_partition = 'your_date' UNION ALL SELECT COUNT(*), COUNT(*), COUNT(*), COUNT(*), COUNT(*), COUNT(*) FROM table4 WHERE date_partition = 'your_date' UNION ALL SELECT COUNT(*), COUNT(*), COUNT(*), COUNT(*), COUNT(*), COUNT(*) FROM table5 WHERE date_partition = 'your_date' UNION ALL SELECT COUNT(*), COUNT(*), COUNT(*), COUNT(*), COUNT(*), COUNT(*) FROM table6 WHERE date_partition = 'your_date' ) SELECT CASE WHEN SUM(count_table1) > 0 AND SUM(count_table2) > 0 AND SUM(count_table3) > 0 AND SUM(count_table4) > 0 AND SUM(count_table5) > 0 AND SUM(count_table6) > 0 THEN (SELECT * FROM table1 WHERE date_partition = 'your_date') ELSE NULL -- or whatever you want to return if data doesn't exist in all tables END AS result FROM data_counts; ... View more

@ChineduLB  Impala doesn't directly support nested select statements within the WHEN clause of a CASE statement. However, you can achieve similar logic Subqueries for conditions: You can use subqueries within the WHEN clause to evaluate conditions based on data retrieved from other tables. SELECT case when (select count(*) from table1) > 0 then (select * from table1) when (select count(*) from table2) > 0 and (select count(*) from table3) > 0 then (select * from table3) else null end as result_table; This query checks if table1 has any rows. If yes, it selects all columns from table1. Otherwise, it checks if both table2 and table3 have rows. If both have data, it selects all columns from table3. If none of the conditions are met, it returns null.   ... View more

You can run the below command: solrctl cluster --get-solrxml /tmp/solr.xml The file will be stored in /tmp/solr.xml ... View more

Hi @ChineduLB , You can use `.groupBy` and `concat_ws(",",collect_list)` functions and to generate `ID` use `row_number` window function.   val df=Seq(("1","User1","Admin"),("2","User1","Accounts"),("3","User2","Finance"),("4","User3","Sales"),("5","User3","Finance")).toDF("ID","USER","DEPT") import org.apache.spark.sql.expressions.Window df.groupBy("USER"). agg(concat_ws(",",collect_list("DEPT")).alias("DEPARTMENT")). withColumn("ID",row_number().over(w)). select("ID","USER","DEPARTMENT").show() ... View more