How can I improve the amount of data queried with

2020-02-13 01:52发布

问题:

I have a BigQuery table - day partitioned, and clustered. However, it still uses a lot of data when I run queries over it. How is this possible?

回答1:

Sometimes no partitions, or weekly/monthly/yearly partitions will work way better than having a daily partitioned table + clustering.

This because each cluster of data in BigQuery has a minimum size. If each day of data in a daily partitioned table has less than that amount of data, you won't see any benefits at all from clustering your table.

For example, let's create a table with 30+ years of weather. I will partition this table by month (to fit multiple years into one table):

CREATE TABLE `temp.gsod_partitioned`
PARTITION BY date_month
CLUSTER BY name
AS 
SELECT *, DATE_TRUNC(date, MONTH) date_month
FROM `fh-bigquery.weather_gsod.all` 

Now, let's run a query over it - using the clustering field name:

SELECT name, state, ARRAY_AGG(STRUCT(date,temp) ORDER BY temp DESC LIMIT 5) top_hot, MAX(date) active_until
FROM `temp.gsod_partitioned`
WHERE name LIKE 'SAN FRANC%'
AND date > '1980-01-01'
GROUP BY 1,2
ORDER BY active_until DESC 
# (2.3 sec elapsed, 3.1 GB processed)

Now, let's do this over an identical table - partitioned by a fake date (so no partitioning really), and clustered by the same column:

SELECT name, state, ARRAY_AGG(STRUCT(date,temp) ORDER BY temp DESC LIMIT 5) top_hot, MAX(date) active_until
FROM `fh-bigquery.weather_gsod.all` 
WHERE name LIKE 'SAN FRANC%'
AND date > '1980-01-01'
GROUP BY 1,2
ORDER BY active_until DESC
# (1.5 sec elapsed, 62.8 MB processed)

Only 62.8 MB of data (vs 3.1GB) were processed!

This because clustering without partitions is much more efficient on tables that don't have a lot of GB per day.

Bonus: Clustered by geo:

SELECT name, state, ARRAY_AGG(STRUCT(date,temp) ORDER BY temp DESC LIMIT 5) top_hot, MAX(date) active_until  
FROM `fh-bigquery.weather_gsod.all_geoclustered`  
WHERE date > '1980-01-01'
AND ST_DISTANCE(point_gis, ST_GEOGPOINT(-122.465, 37.807)) < 40000
GROUP BY 1,2
ORDER BY ST_DISTANCE(ANY_VALUE(point_gis), ST_GEOGPOINT(-122.465, 37.807))
# (2.1 sec elapsed, 100.7 MB processed)