explain.depesz.com

PostgreSQL's explain analyze made readable

Result: hieg

Settings
# exclusive inclusive rows x rows loops node
1. 0.000 76,009.144 ↓ 8.0 8 1

Sort (cost=284,653.58..284,653.58 rows=1 width=273) (actual time=76,009.141..76,009.144 rows=8 loops=1)

  • Sort Key: accounts.followers_count
  • Sort Method: quicksort Memory: 29kB
2. 64.631 76,051.247 ↓ 8.0 8 1

Gather (cost=160,738.90..284,653.57 rows=1 width=273) (actual time=73,798.354..76,051.247 rows=8 loops=1)

  • Workers Planned: 2
  • Workers Launched: 2
3. 5,475.416 75,986.616 ↓ 3.0 3 3 / 3

Parallel Hash Left Join (cost=159,738.90..283,653.47 rows=1 width=273) (actual time=72,718.682..75,986.616 rows=3 loops=3)

  • Hash Cond: ((tweets.id)::text = (tweet_hashtags.tweet_id)::text)
  • Filter: (tweet_hashtags.id IS NULL)
  • Rows Removed by Filter: 3
4. 52.803 65,655.378 ↓ 3.0 3 3 / 3

Nested Loop (cost=95,343.62..212,156.17 rows=1 width=292) (actual time=39,615.546..65,655.378 rows=3 loops=3)

5. 1,377.825 27,930.808 ↓ 45.9 10,456 3 / 3

Parallel Hash Join (cost=95,343.06..211,787.83 rows=228 width=142) (actual time=13,350.620..27,930.808 rows=10,456 loops=3)

  • Hash Cond: (tweet_mentions.account_id = accounts.id)
6. 13,422.803 13,422.803 ↑ 1.3 2,412,554 3 / 3

Parallel Seq Scan on tweet_mentions (cost=0.00..108,510.97 rows=3,022,397 width=28) (actual time=218.879..13,422.803 rows=2,412,554 loops=3)

7. 265.072 13,130.180 ↓ 7.7 839 3 / 3

Parallel Hash (cost=95,341.70..95,341.70 rows=109 width=122) (actual time=13,130.179..13,130.180 rows=839 loops=3)

  • Buckets: 4,096 (originally 1024) Batches: 1 (originally 1) Memory Usage: 632kB
8. 12,865.108 12,865.108 ↓ 7.7 839 3 / 3

Parallel Seq Scan on accounts (cost=0.00..95,341.70 rows=109 width=122) (actual time=46.932..12,865.108 rows=839 loops=3)

  • Filter: (description ~~* '%comedian%'::text)
  • Rows Removed by Filter: 1,155,302
9. 37,671.767 37,671.767 ↓ 0.0 0 31,367 / 3

Index Scan using tweets_pk on tweets (cost=0.56..1.62 rows=1 width=170) (actual time=3.603..3.603 rows=0 loops=31,367)

  • Index Cond: ((id)::text = (tweet_mentions.tweet_id)::text)
  • Filter: ((content ~~* '%conspiracy%'::text) AND ((retweet_count <= 10) OR (retweet_count >= 50)))
  • Rows Removed by Filter: 1
10. 760.317 4,855.822 ↑ 1.3 969,322 3 / 3

Parallel Hash (cost=42,149.57..42,149.57 rows=1,211,657 width=24) (actual time=4,855.822..4,855.822 rows=969,322 loops=3)

  • Buckets: 262,144 Batches: 16 Memory Usage: 12,096kB
11. 4,095.505 4,095.505 ↑ 1.3 969,322 3 / 3

Parallel Seq Scan on tweet_hashtags (cost=0.00..42,149.57 rows=1,211,657 width=24) (actual time=109.662..4,095.505 rows=969,322 loops=3)

Planning time : 124.038 ms
Execution time : 76,060.216 ms