在 Spark SQL 中交叉连接计算 [英] Cross Join for calculation in Spark SQL

问题描述

我有一个只有 1 记录/值的临时视图，我想使用该值来计算另一个大表中存在的客户的年龄(100M 行).我使用了 CROSS JOIN 子句，这导致了性能问题.

I have a temporary view with only 1 record/value and I want to use that value to calculate the age of the customers present in another big table (with 100M rows). I used a CROSS JOIN clause, which is resulting in a performance issue.

有没有更好的方法来实现这个要求，它会表现得更好?broadcast 提示是否适用于这种情况?处理此类情况的推荐方法是什么?

Is there a better approach to implement this requirement which is will perform better ? Will a broadcast hint be suitable in this scenario ? What is the recommended approach to tackle such scenarios ?

参考表:(仅包含1值)

create temporary view ref
as
select to_date(refdt, 'dd-MM-yyyy') as refdt --returns only 1 value
from tableA
where logtype = 'A';

客户表(1000 万行):

Cust table (10 M rows):

custid | birthdt
A1234  | 20-03-1980
B3456  | 09-05-1985
C2356  | 15-12-1990

查询(计算年龄 w.r.t birthdt):

Query (calculate age w.r.t birthdt):

select 
a.custid, 
a.birthdt, 
cast((datediff(b.ref_dt, a.birthdt)/365.25) as int) as age
from cust a
cross join ref b;

我的问题是 - 有没有更好的方法来实现这个要求?

My question is - Is there a better approach to implement this requirement ?

谢谢

推荐答案

很难准确理解你的观点，但如果你不能使用 Scala 或 pyspark 和 >dataframes 和 .cache 等然后我认为不要使用 temporary view，只需创建一个单行 table.我的印象是你在笔记本中使用 Spark %sql，比如 Databricks.

Hard to work out exactly your point, but if you cannot use Scala or pyspark and dataframes with .cache etc. then I think that instead of of using a temporary view, just create a single row table. My impression is you are using Spark %sql in a notebook on, say, Databricks.

这是我的怀疑.

也就是说，broadcastjoin 提示很可能意味着优化器只发送 1 行.请参阅 https:///jaceklaskowski.gitbooks.io/mastering-spark-sql/content/spark-sql-hint-framework.html#specifying-query-hints

That said a broadcastjoin hint may well mean the optimizer only sends out 1 row. See https://jaceklaskowski.gitbooks.io/mastering-spark-sql/content/spark-sql-hint-framework.html#specifying-query-hints

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