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Performance Issue: Slow Query Execution Despite Using LIMIT #3274

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fredrikIOT opened this issue Jan 31, 2024 · 7 comments
Open

Performance Issue: Slow Query Execution Despite Using LIMIT #3274

fredrikIOT opened this issue Jan 31, 2024 · 7 comments
Labels
A-storage Involves code in storage engines C-performance Category Performance

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@fredrikIOT
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What type of bug is this?

Performance issue

What subsystems are affected?

Standalone mode

Minimal reproduce step

  1. Populate a test database with data simulating 20000 sensors across 50 locations, with each location having its own table and each sensor having its own tag.
  2. Insert data at a rate of 20000 data points per second (400 for each table), spread over 50 tables.
  3. Run this simulation continuously for a few days.
  4. Execute the query SELECT * FROM "location1" ORDER BY ts DESC LIMIT 100;.

What did you expect to see?

Expected efficient use of LIMIT and OFFSET, where the query execution should be quick, only processing the first 100 rows.

What did you see instead?

The query execution is slow, taking multiple seconds (8634 ms) despite using LIMIT. It seems that the LIMIT clause does not stop the query processing after reaching the limit but only restricts the number of rows returned.

Performance Metrics:

  • When running SELECT * FROM "location1" ORDER BY ts DESC LIMIT 100;. Metrics:
Returned Metrics
Selected 100 rows in 8634 ms
  • For comparison: When query the count of the table using SELECT count(*) FROM "location1";:
Returned Metrics Number of rows (result of the query)
Selected 1 rows in 2333 ms 181459600

SQL Analyze:

EXPLAIN ANALYZE 
SELECT * FROM "location1" limit 5 offset 1 

Result:

plan_type plan
Plan with Metrics MergeScanExec: peers=[4475355922432(1042, 0), ], metrics=[output_rows=100, ready_time=87.566768ms, finish_time=4.524580126s, first_consume_time=4.524555159s]

What operating system did you use?

Docker (Ubuntu)

What version of GreptimeDB did you use?

docker image: greptime/greptimedb:nightly-20240126-8bade8f8e4

Relevant log output and stack trace

No response

@waynexia
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Hi @fredrikIOT, appreciate your detailed feedback!

I noticed you also run SELECT * FROM "location1" limit 5 offset 1 and it's slower than SELECT count(*) FROM "location1"; I'm wondering if it is reproducible? And how large is the result set? According to the analyze result it has output_rows=100 100 rows. Would the SQL SELECT * FROM "location1" limit 5 offset 1 return 100 rows (without the ANALYZE) or 5 rows

@MichaelScofield
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@fredrikIOT Can you share the SQL of creating table "location1"?

@fredrikIOT
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fredrikIOT commented Feb 1, 2024

Hi @fredrikIOT, appreciate your detailed feedback!

I noticed you also run SELECT * FROM "location1" LIMIT 5 offset 1 and it's slower than SELECT count(*) FROM "location1"; I'm wondering if it is reproducible? And how large is the result set? According to the analyze result it has output_rows=100 100 rows. Would the SQL SELECT * FROM "location1" limit 5 offset 1 return 100 rows (without the ANALYZE) or 5 rows

@waynexia I need to correct an error in my previous message. I referenced the wrong query and result. Here's the accurate information:
Correct Query:
EXPLAIN ANALYZE SELECT * FROM "location1" ORDER BY ts DESC LIMIT 5 offset 1
Correct Result:
MergeScanExec: peers=[4629974745088(1078, 0), ], metrics=[output_rows=5, ready_time=379.715193ms, finish_time=9.498069549s, first_consume_time=9.498045694s]

While reviewing this, I've noticed the significant impact of the ORDER BY clause on the query performance. Here are some observations:

  • SELECT * FROM "location1" ORDER BY ts DESC LIMIT 5 offset 1 uses 5372 ms
  • SELECT * FROM "location1" LIMIT 5 offset 1 uses 213 ms
  • SELECT COUNT(*) FROM "location1"; uses 2787 ms

So, I guess the question of whether COUNT takes more time than LIMIT is no longer valid. However, it is reproducible that COUNT is slower when using ORDER BY.

@fredrikIOT
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fredrikIOT commented Feb 1, 2024

@fredrikIOT Can you share the SQL of creating table "location1"?

@MichaelScofield Here's the SQL for creating the "location1" table:

CREATE TABLE IF NOT EXISTS "location1" (
  "location_uid" STRING NULL,
  "room_uid" STRING NULL,
  "log_uid" STRING NULL,
  "sensor_name" STRING NULL,
  "value" DOUBLE NULL,
  "ts" TIMESTAMP(3) NOT NULL,
  TIME INDEX ("ts"),
  PRIMARY KEY ("location_uid", "room_uid", "log_uid", "sensor_name")
) ENGINE=mito WITH(regions = 1)

As I mentioned in my previous message, the performance issue seems to be primarily due to the ORDER BY clause. However, having the table structure might provide further insights into any other potential performance implications.

@waynexia
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waynexia commented Feb 2, 2024

So, I guess the question of whether COUNT takes more time than LIMIT is no longer valid. However, it is reproducible that COUNT is slower when using ORDER BY.

Yes, that's correct. The main reason that SELECT count(*) FROM "location1"; runs faster than SELECT * FROM "location1" ORDER BY ts DESC LIMIT 100; is the ORDER BY ts. Unfortunately we haven't optimized for this scenario -- though we know it's important for time series scenarios. We used to have one optimization that could speed up ORDER BY ts by a fascinating percentage, but it's not adapted yet after a major refactor 🫣

We can keep this issue open as a tracker.

@killme2008
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Do we have any plan to optimize for this case? @waynexia @evenyag

@evenyag
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evenyag commented Mar 4, 2024

I'm afraid that I don't have enough time to finish it in v0.8, maybe I can optimize some cases in v0.9.

@evenyag evenyag added C-performance Category Performance A-storage Involves code in storage engines labels Mar 27, 2024
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