If you are using Spark > 1.5, the best way is to use DataFrame API directly,
instead of SQL. In dataframe, you can specify the boardcast join hint in the
dataframe API, which will force the boardcast join.
Yong
From: mich.talebza...@gmail.com
Date: Mon, 20 Jun 2016 13:09:17 +0100
Subject: Re: Is it possible to turn a SortMergeJoin into BroadcastHashJoin?
To: linguin....@gmail.com
CC: zhen...@dtdream.com; user@spark.apache.org
what sort of the tables are these?
Can you register the result set as temp table and do a join on that assuming
the RS is going to be small
s.filter(($"c2" < 1000)).registerTempTable("tmp")
and then do a join between tmp and Table2
HTH
Dr Mich Talebzadeh
LinkedIn
https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
http://talebzadehmich.wordpress.com
On 20 June 2016 at 12:38, Takeshi Yamamuro <linguin....@gmail.com> wrote:
Seems it is hard to predict the output size of filters because the current
spark has limited statistics of input data. A few hours ago, Reynold created a
ticket for cost-based optimizer framework in
https://issues.apache.org/jira/browse/SPARK-16026.If you have ideas, questions,
and suggestions, feel free to join the discussion.
// maropu
On Mon, Jun 20, 2016 at 8:21 PM, 梅西0247 <zhen...@dtdream.com> wrote:
Thanks for your reply, In fact, that is what i just did....
But my question is: Can we change the spark join behavior more clever, to turn
a sortmergejoin into broadcasthashjoin automatically when if "found" that a
output RDD is small enough?
------------------------------------------------------------------发件人：Takeshi
Yamamuro <linguin....@gmail.com>发送时间：2016年6月20日(星期一) 19:16收件人：梅西0247
<zhen...@dtdream.com>抄 送：user <user@spark.apache.org>主 题：Re: Is it possible to
turn a SortMergeJoin into BroadcastHashJoin?
Hi,
How about caching the result of `select * from a where a.c2 < 1000`, then
joining them?You probably need to tune `spark.sql.autoBroadcastJoinThreshold`
to enable broadcast joins for the result table.
// maropu
On Mon, Jun 20, 2016 at 8:06 PM, 梅西0247 <zhen...@dtdream.com> wrote:
Hi everyone,
I ran a SQL join statement on Spark 1.6.1 like this:
select * from table1 a join table2 b on a.c1 = b.c1 where a.c2 < 1000;and it
took quite a long time because It is a SortMergeJoin and the two tables are big.
In fact, the size of filter result(select * from a where a.c2 < 1000) is very
small, and I think a better solution is to use a BroadcastJoin with the filter
result, but I know the physical plan is static and it won't be changed.
So, can we make the physical plan more adaptive? (In this example, I mean using
a BroadcastHashJoin instead of SortMergeJoin automatically. )
--
---
Takeshi Yamamuro
--
---
Takeshi Yamamuro
