sql - How to remove duplicated row by timestamp in BigQuery?

Sql - How to remove duplicated row by timestamp in BigQuery?

To remove duplicate rows based on a timestamp column in BigQuery, you can use a combination of window functions and a common table expression (CTE). Here's a step-by-step approach:

Example Scenario

Assume you have a table named your_table in BigQuery with columns:

  • id: Unique identifier for each row.
  • timestamp_column: Timestamp column based on which you want to remove duplicates.
  • Other columns that define the content of each row.

SQL Query to Remove Duplicates

WITH deduplicated_data AS ( SELECT id, timestamp_column, other_columns, ROW_NUMBER() OVER (PARTITION BY timestamp_column ORDER BY timestamp_column DESC) AS row_number FROM your_table ) SELECT id, timestamp_column, other_columns FROM deduplicated_data WHERE row_number = 1;

Explanation:

  1. Common Table Expression (CTE): deduplicated_data

    • Uses ROW_NUMBER() OVER (PARTITION BY timestamp_column ORDER BY timestamp_column DESC) to assign a row number to each row within each partition defined by timestamp_column.
    • PARTITION BY timestamp_column ensures that rows with the same timestamp_column are grouped together.
    • ORDER BY timestamp_column DESC orders rows within each partition by timestamp_column in descending order, so the row with the latest timestamp (highest value) gets row_number = 1.

  2. Main Query:

    • Selects columns (id, timestamp_column, other_columns) from the deduplicated_data CTE.
    • Filters rows where row_number = 1, which means it selects only the row with the latest timestamp for each group of timestamp_column.

Notes:

  • Timestamp Column: Replace timestamp_column with the actual name of your timestamp column.
  • ROW_NUMBER Function: This function assigns a unique sequential integer to each row within its partition. Rows with the same timestamp_column will have consecutive numbers starting from 1 based on the specified ordering (ORDER BY clause).
  • Performance Considerations: Ensure your timestamp_column is indexed or partitioned for better performance, especially with large datasets.

Handling Ties:

If you have ties in timestamps (multiple rows with the same timestamp and you want to include all tied rows), you can use RANK() instead of ROW_NUMBER():

WITH deduplicated_data AS ( SELECT id, timestamp_column, other_columns, RANK() OVER (PARTITION BY timestamp_column ORDER BY timestamp_column DESC) AS rank FROM your_table ) SELECT id, timestamp_column, other_columns FROM deduplicated_data WHERE rank = 1;

RANK() will assign the same rank to rows with the same timestamp, whereas ROW_NUMBER() will assign unique sequential numbers.

Conclusion:

By using window functions like ROW_NUMBER() or RANK() in a CTE, you can effectively remove duplicate rows based on a timestamp column in BigQuery. Adjust the column names (id, timestamp_column, other_columns) and table name (your_table) according to your specific schema.

Examples

  1. Delete duplicated rows by timestamp in BigQuery

    • Description: Delete duplicate rows based on timestamp in BigQuery using a common table expression (CTE).
    • Code:
      WITH DeduplicatedData AS ( SELECT *, ROW_NUMBER() OVER(PARTITION BY timestamp_column ORDER BY timestamp_column) AS row_number FROM `your_dataset.your_table` ) DELETE FROM DeduplicatedData WHERE row_number > 1;
    • Explanation: This query identifies duplicate rows based on the timestamp_column using ROW_NUMBER() window function within a CTE. It assigns a row number to each row partitioned by timestamp_column and orders by timestamp_column. Rows with row_number > 1 are then deleted, keeping only one unique row per timestamp.

  2. Select distinct rows by timestamp in BigQuery

    • Description: Select distinct rows based on timestamp in BigQuery, effectively removing duplicates.
    • Code:
      SELECT DISTINCT * FROM `your_dataset.your_table` ORDER BY timestamp_column;
    • Explanation: This query retrieves distinct rows from your_table based on timestamp_column, ensuring only unique rows are returned. It orders the results by timestamp_column.

  3. Remove duplicates using GROUP BY and MAX aggregation in BigQuery

    • Description: Remove duplicates by timestamp using GROUP BY and MAX aggregation to keep the latest timestamp.
    • Code:
      SELECT * FROM ( SELECT *, ROW_NUMBER() OVER(PARTITION BY timestamp_column ORDER BY timestamp_column DESC) AS row_number FROM `your_dataset.your_table` ) WHERE row_number = 1;
    • Explanation: This query uses ROW_NUMBER() with PARTITION BY timestamp_column to assign row numbers ordered by descending timestamp_column. It selects rows where row_number = 1, effectively keeping only the row with the latest timestamp per group.

  4. Delete duplicates using self-join and timestamp comparison in BigQuery

    • Description: Delete duplicate rows by comparing timestamps using a self-join in BigQuery.
    • Code:
      DELETE FROM `your_dataset.your_table` t1 WHERE EXISTS ( SELECT 1 FROM `your_dataset.your_table` t2 WHERE t1.primary_key = t2.primary_key AND t1.timestamp_column > t2.timestamp_column );
    • Explanation: This delete statement removes rows from your_table (t1) where another row (t2) with the same primary_key but an earlier timestamp_column exists. It ensures only the row with the latest timestamp remains for each primary_key.

  5. Select distinct rows using DISTINCT and timestamp_column in BigQuery

    • Description: Select distinct rows based on timestamp_column to eliminate duplicates in BigQuery.
    • Code:
      SELECT DISTINCT * FROM `your_dataset.your_table` ORDER BY timestamp_column;
    • Explanation: This query uses DISTINCT to fetch unique rows from your_table based on timestamp_column, ensuring only one row per distinct timestamp is returned. It orders the results by timestamp_column.

  6. Remove duplicates with PARTITION BY and timestamp comparison in BigQuery

    • Description: Use PARTITION BY and timestamp comparison to remove duplicates in BigQuery.
    • Code:
      WITH DeduplicatedData AS ( SELECT *, ROW_NUMBER() OVER(PARTITION BY timestamp_column ORDER BY timestamp_column DESC) AS row_number FROM `your_dataset.your_table` ) DELETE FROM DeduplicatedData WHERE row_number > 1;
    • Explanation: This query uses a CTE (DeduplicatedData) with ROW_NUMBER() partitioned by timestamp_column and ordered by descending timestamp_column. It deletes rows where row_number > 1, keeping only the latest timestamped row for each group.

  7. Select distinct rows by timestamp using GROUP BY and MAX in BigQuery

    • Description: Select distinct rows based on timestamp using GROUP BY and MAX aggregation in BigQuery.
    • Code:
      SELECT * FROM `your_dataset.your_table` WHERE (timestamp_column, primary_key) IN ( SELECT MAX(timestamp_column), primary_key FROM `your_dataset.your_table` GROUP BY primary_key );
    • Explanation: This query selects rows from your_table where the combination of timestamp_column and primary_key matches the maximum timestamp_column for each primary_key, effectively filtering out duplicates.

  8. Remove duplicates by timestamp using ROW_NUMBER and PARTITION BY in BigQuery

    • Description: Remove duplicate rows based on timestamp using ROW_NUMBER() and PARTITION BY in BigQuery.
    • Code:
      DELETE FROM `your_dataset.your_table` WHERE (primary_key, timestamp_column) NOT IN ( SELECT primary_key, timestamp_column FROM ( SELECT primary_key, timestamp_column, ROW_NUMBER() OVER(PARTITION BY primary_key ORDER BY timestamp_column DESC) AS row_number FROM `your_dataset.your_table` ) WHERE row_number = 1 );
    • Explanation: This delete statement removes rows from your_table where (primary_key, timestamp_column) does not match the row number 1 within each primary_key partition, ensuring only the latest timestamped row per primary_key remains.

  9. Select distinct rows by timestamp using LEAD function in BigQuery

    • Description: Select distinct rows based on timestamp using LEAD function for deduplication in BigQuery.
    • Code:
      SELECT * FROM ( SELECT *, LEAD(timestamp_column) OVER(PARTITION BY primary_key ORDER BY timestamp_column) AS next_timestamp FROM `your_dataset.your_table` ) WHERE timestamp_column != next_timestamp OR next_timestamp IS NULL;
    • Explanation: This query uses LEAD() with PARTITION BY primary_key to retrieve the next timestamp_column value. It selects rows where timestamp_column is not equal to next_timestamp or next_timestamp is NULL, effectively keeping only distinct rows based on timestamp_column within each primary_key group.

  10. Remove duplicates with timestamp comparison and self-join in BigQuery

    • Description: Remove duplicate rows by timestamp comparison using a self-join in BigQuery.
    • Code:
      DELETE FROM `your_dataset.your_table` t1 WHERE EXISTS ( SELECT 1 FROM `your_dataset.your_table` t2 WHERE t1.primary_key = t2.primary_key AND t1.timestamp_column < t2.timestamp_column );
    • Explanation: This delete statement removes rows from your_table (t1) where there exists another row (t2) with the same primary_key but a later (t1.timestamp_column < t2.timestamp_column) timestamp_column. It ensures only the most recent timestamped row per primary_key remains.

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