2. 2
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Contents
Clustering 03
When to apply clustering 04
How to apply clustering 05
Scenario 1 07
Scenario 2 10
Limitations 17
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3. 3
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● Purpose: Limits the amount of data that needs to be read while executing a query.
● Benefits
○ Improved query performance when filtering (WHERE or JOIN) or aggregation (GROUP BY) by clustered
columns
○ Reduced cost when filtering or aggregation by clustered columns
● How?
○ Sorts storage blocks based on the values of the clustered columns.
○ Useful when the clustered columns have high cardinality.
○ Scans only the relevant blocks of clustered columns as specified by the filter or group by clause.
○ No accurate query cost estimate before running the query.
Clustering
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● Queries commonly filter on particular columns
● Filtered columns have high cardinality (many distinct values)
When to apply clustering?
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● Clustered column types
○ STRING, INT64, NUMERIC, BIGNUMERIC, DATE, DATETIME, TIMESTAMP, BOOL, GEOGRAPHY
● Clustered column order is important
○ Query filter order must match the clustered column order
○ The first clustered column must be included in the query filter.
How to apply clustering?
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6. 6
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CREATE TABLE `gcp-wow-wiq-dclo-test.sql_tuning.stackoverflow_posts_cluster_creation_date_view_count`
(
id INTEGER,
title STRING,
answer_count INTEGER,
creation_date TIMESTAMP,
view_count INTEGER
)
CLUSTER BY
creation_date,
view_count;
How to create a clustered table?
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7. 7
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Select the
- ID
- Title
- Answer count
of Stackoverflow posts
Where the creation date is between 01 Oct 2008 and 01 Dec 2008.
Scenario 1
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8. 8
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56 seconds
Slot time consumed
Query performance without clustering
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9. 9
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27 seconds
Slot time consumed
Query performance with clustering
(creation date as clustered column)
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Clustering improves performance by 2X
10. 10
We unlock the power of data to reimagine retail
Select the
- ID
- Title
- Answer count
of Stackoverflow posts
Where the creation date is between 01 Oct 2008 and 01 Dec 2008
and view count >= 100.
Scenario 2
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11. 11
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1 minute 9 seconds
Slot time consumed
Query performance without clustering
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12. 12
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21 seconds
Slot time consumed
Query performance with clustering
(creation date as clustered column)
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Clustering by the first filter column
improves performance by 3X
13. 13
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574 milliseconds
Slot time consumed
Query performance with clustering
(creation date, view count as clustered columns)
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Clustering by the both filter columns
improves performance by 120X
14. 14
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15 seconds(worse)
Slot time consumed
Query performance with clustering - reverse filtering order
(creation date, view count as clustered columns)
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Reverse order of the clustered columns
in the query filter does not yield optimal
performance.
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2 minutes 45 seconds (not optimal)
Slot time consumed
Query performance with clustering - filter by view count only
(creation date, view count as clustered columns)
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Excluding the first clustered column
in the query filter does not yield
optimal performance.
16. 16
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4 minutes 38 seconds
Slot time consumed
Query performance without clustering - filter by view count only
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17. 17
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2 minutes 29 seconds (optimal)
Slot time consumed
Query performance with clustering - filter by view count only
(view count as clustered column)
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Including view_count clustered
column in the query filter yields
optimal performance.
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● Only Google SQL is supported.
● At most 4 clustered columns per table.
● When clustering by the STRING type column, only the first 1024 characters are used for clustering.
● When clustering an table with existing data, the existing data is not clustered; only new data is clustered
and is subject to automatic reclustering.
Limitations
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19. 19
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1. Introduction to Clustered tables
2. Create and use clustered tables
References
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