按周/月/季度/年分区以超过分区限制? [英] Partition by week/month//quarter/year to get over the partition limit?

问题描述

我有 32 年的数据要放入分区表中.但是 BigQuery 说我超过了限制(4000 个分区).

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).

对于像这样的查询:

CREATE TABLE `deleting.day_partition`
PARTITION BY FlightDate 
AS 
SELECT *
FROM `flights.original` 

我收到如下错误:

查询产生的分区太多，允许2000，查询至少产生11384个分区

Too many partitions produced by query, allowed 2000, query produces at least 11384 partitions

我怎样才能突破这个限制?

How can I get over this limit?

推荐答案

你可以按周/月/年分区，而不是按天分区.

Instead of partitioning by day, you could partition by week/month/year.

在我的例子中，每年的数据包含大约 3GB 的数据，所以如果我按年分区，我将从聚类中获得最大的好处.

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.

为此，我将创建一个 year 日期列，并按它分区:

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`

请注意，我在此过程中创建了额外的列 DATE_TRUNC(FlightDate, YEAR) AS FlightDate_year.

Note that I created the extra column DATE_TRUNC(FlightDate, YEAR) AS FlightDate_year in the process.

表统计:

既然表是集群的，我就得到好处分区，即使我不使用分区列(年份)作为过滤器:

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

这篇关于按周/月/季度/年分区以超过分区限制?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！