Optimizing DISTANCE using projections

zun · May 2022

Hi folks,

I am currently using the DISTANCE function in vertica. I'm not getting great performance, so wanted to get your opinion on if this can be optimized. If anyone has optimized DISTANCE using projections before, your opinion would be greatly appreciated.

My Query:

SELECT Date_trunc('month', modified_date),
      APPROXIMATE_COUNT_DISTINCT(userId)  AS distinct_user_count
FROM   mySchema.userProjection
WHERE modified_date BETWEEN '2021-01-01' AND '2022-01-31'
       AND country = 'US'
       AND DISTANCE(40.71427, -74.00597, userLatitude, userLongitude) < 160
GROUP BY 1 ORDER BY 1

My Projection:

CREATE PROJECTION mySchema.userProjection
    (
     country ENCODING RLE,
     modified_date ENCODING ZSTD_FAST_COMP,
     userLatitude ENCODING ZSTD_FAST_COMP,
     userLongitude ENCODING ZSTD_FAST_COMP,
     userId ENCODING ZSTD_FAST_COMP
     )
    AS
        SELECT myTable.country,
               myTable.modified_date,
               myTable.userLatitude,
               myTable.userLongitude,
               myTable.userId,
        FROM mySchema.myTable
        ORDER BY myTable.country,
                 myTable.userLatitude,
                 myTable.userLongitude
    SEGMENTED BY hash(myTable.country, myTable.userId, myTable.modified_date) ALL NODES;

The table is partitioned by modified_date. Query currently takes about 16s, I was really aiming for <5s.

My guess is DISTANCE might not be using the projection correctly.

Appreciate any help!

Hibiki · July 2022

Can you check which operator took time? Does myTable have modified_date column?

zun · October 2022

@Hibiki How can I figure out which operator took more time? Yes, the table has a modified_date column. The table is partitioned on modified_date (specifically partitioned on Date_trunc('month', modified_date))

Hibiki · October 2022

Please collect the query profile by using PROFILE clause.

PROFILE
SELECT Date_trunc('month', modified_date),
       APPROXIMATE_COUNT_DISTINCT(userId)  AS distinct_user_count
FROM   mySchema.userProjection
WHERE  modified_date BETWEEN '2021-01-01' AND '2022-01-31'
       AND country = 'US'
       AND DISTANCE(40.71427, -74.00597, userLatitude, userLongitude) < 160
GROUP BY 1 ORDER BY 1;

You can see the transaction ID and statement ID as below.

HINT:  Select * from v_monitor.execution_engine_profiles where transaction_id=45035996766964481 and statement_id=1;

Then, please execute the following query to collect the time for each operator.

SELECT
  path_id,
  operator_name,
  SUM(CASE WHEN counter_name = 'execution time (us)' THEN counter_value ELSE 0 END) exec_time_us,
  SUM(CASE WHEN counter_name = 'clock time (us)' THEN counter_value ELSE 0 END) clock_time_us
FROM
  v_monitor.execution_engine_profiles
WHERE
  transaction_id = 45035996766964481
  AND statement_id = 1
GROUP BY 1, 2
ORDER BY 1, 2;

You can get the query plan as well by the following query.

SELECT
  path_id,
  path_line
FROM
  v_monitor.query_plan_profiles
WHERE
  transaction_id = 45035996766964481
  AND statement_id = 1
ORDER BY
  path_id,
  path_line_index;

Please replace the transaction ID and statement ID by yours.

Optimizing DISTANCE using projections

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