Partition by week/month//quarter/year to get over the partition limit? - google-bigquery

Question

I have 32 years of data that I want to put into a partitioned table. However BigQuery says that I'm going over the limit (4000 partitions).
For a query like:
CREATE TABLE `deleting.day_partition`
PARTITION BY FlightDate
AS
SELECT *
FROM `flights.original`
I'm getting an error like:
Too many partitions produced by query, allowed 2000, query produces at least 11384 partitions
How can I get over this limit?

Answer 1

Instead of partitioning by day, you could partition by week/month/year.
In my case each year of data contains around ~3GB of data, so I'll get the most benefits from clustering if I partition by year.
For this, I'll create a year date column, and partition by it:
CREATE TABLE `fh-bigquery.flights.ontime_201903`
PARTITION BY FlightDate_year
CLUSTER BY Origin, Dest
AS
SELECT *, DATE_TRUNC(FlightDate, YEAR) FlightDate_year
FROM `fh-bigquery.flights.raw_load_fixed`
Note that I created the extra column DATE_TRUNC(FlightDate, YEAR) AS FlightDate_year in the process.
Table stats:
Since the table is clustered, I'll get the benefits of partitioning even if I don't use the partitioning column (year) as a filter:
SELECT *
FROM `fh-bigquery.flights.ontime_201903`
WHERE FlightDate BETWEEN '2008-01-01' AND '2008-01-10'
Predicted cost: 83.4 GB
Actual cost: 3.2 GB

Answer 2

Alternative example, I created a NOAA GSOD summary table clustered by station name - and instead of partitioning by day, I didn't partition it at all.
Let's say I want to find the hottest days since 1980 for all stations with a name like SAN FRAN%:
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
Note that I got the results after processing only 55.2MB of data.
The equivalent query on the source tables (without clustering) processes 4GB instead:
# query on non-clustered tables - too much data compared to the other one
SELECT name, state, ARRAY_AGG(STRUCT(CONCAT(a.year,a.mo,a.da),temp) ORDER BY temp DESC LIMIT 5) top_hot, MAX(CONCAT(a.year,a.mo,a.da)) active_until
FROM `bigquery-public-data.noaa_gsod.gsod*` a
JOIN `bigquery-public-data.noaa_gsod.stations` b
ON a.wban=b.wban AND a.stn=b.usaf
WHERE name LIKE 'SAN FRANC%'
AND _table_suffix >= '1980'
GROUP BY 1,2
ORDER BY active_until DESC
I also added a geo clustered table, to search by location instead of station name. See details here: https://stackoverflow.com/a/34804655/132438