cancel
Showing results for 
Search instead for 
Did you mean: 
Data Engineering
Join discussions on data engineering best practices, architectures, and optimization strategies within the Databricks Community. Exchange insights and solutions with fellow data engineers.
cancel
Showing results for 
Search instead for 
Did you mean: 

SELECT issue after an OPTIMIZE operation

alxsbn
New Contributor III

I have a strange issue after an OPTIMIZE, no results are returned anymore.

I can time travel over the version easily but passed this data nothing when I'm doing a simple SELECT *.

But I still got a result when I'm doing a SELECT count(*).

How is this possible?  

1 ACCEPTED SOLUTION

Accepted Solutions

Kaniz_Fatma
Community Manager
Community Manager

Hi @alxsbnAfter performing an OPTIMIZE operation, you’ve encountered an interesting situation where no results are returned when you execute a simple SELECT * query, but you still get results when you run SELECT COUNT(*).

Let’s explore this further:

  1. SELECT * vs. SELECT COUNT(*):

    • SELECT * retrieves all columns and rows from the specified table.
    • SELECT COUNT(*) calculates the total number of rows in the table without retrieving the actual data.
  2. Possible Explanations:

    • Index Usage: When you perform SELECT COUNT(*), the database engine can use an index (if available) to quickly determine the row count. However, for SELECT *, it needs to retrieve the actual data, which might involve a full table scan.
    • Data Retrieval Cost: Fetching all columns for every row can be expensive in terms of I/O and memory. If there’s a large amount of data, it could lead to performance issues.
    • Filter Conditions: Check if there are any filter conditions (e.g., WHERE clauses) in your SELECT * query. These conditions might exclude all rows after the OPTIMIZE operation.
    • Data Corruption: Rarely, an OPTIMIZE operation could cause data corruption or inconsistencies. Verify the integrity of your data.
  3. Optimization Strategies:

    • Index Optimization: Ensure that relevant columns have appropriate indexes. Indexes can significantly improve query performance.
    • Analyze Execution Plans: Examine the execution plans for both queries. This will help identify bottlenecks and potential areas for optimization.
    • Statistics Update: Update table statistics to help the query optimizer make better decisions.
    • Check for Locks: Ensure there are no locks preventing data retrieval.
  4. Next Steps:

    • Review your query execution plans and analyze any differences between the two queries.
    • Consider using specific column names instead of SELECT * to retrieve only necessary data.
    • Verify the integrity of your data after the OPTIMIZE operation.
 

View solution in original post

1 REPLY 1

Kaniz_Fatma
Community Manager
Community Manager

Hi @alxsbnAfter performing an OPTIMIZE operation, you’ve encountered an interesting situation where no results are returned when you execute a simple SELECT * query, but you still get results when you run SELECT COUNT(*).

Let’s explore this further:

  1. SELECT * vs. SELECT COUNT(*):

    • SELECT * retrieves all columns and rows from the specified table.
    • SELECT COUNT(*) calculates the total number of rows in the table without retrieving the actual data.
  2. Possible Explanations:

    • Index Usage: When you perform SELECT COUNT(*), the database engine can use an index (if available) to quickly determine the row count. However, for SELECT *, it needs to retrieve the actual data, which might involve a full table scan.
    • Data Retrieval Cost: Fetching all columns for every row can be expensive in terms of I/O and memory. If there’s a large amount of data, it could lead to performance issues.
    • Filter Conditions: Check if there are any filter conditions (e.g., WHERE clauses) in your SELECT * query. These conditions might exclude all rows after the OPTIMIZE operation.
    • Data Corruption: Rarely, an OPTIMIZE operation could cause data corruption or inconsistencies. Verify the integrity of your data.
  3. Optimization Strategies:

    • Index Optimization: Ensure that relevant columns have appropriate indexes. Indexes can significantly improve query performance.
    • Analyze Execution Plans: Examine the execution plans for both queries. This will help identify bottlenecks and potential areas for optimization.
    • Statistics Update: Update table statistics to help the query optimizer make better decisions.
    • Check for Locks: Ensure there are no locks preventing data retrieval.
  4. Next Steps:

    • Review your query execution plans and analyze any differences between the two queries.
    • Consider using specific column names instead of SELECT * to retrieve only necessary data.
    • Verify the integrity of your data after the OPTIMIZE operation.
 
Join 100K+ Data Experts: Register Now & Grow with Us!

Excited to expand your horizons with us? Click here to Register and begin your journey to success!

Already a member? Login and join your local regional user group! If there isn’t one near you, fill out this form and we’ll create one for you to join!