Thanks. You are right on both counts
1. Doing max(instnc_id) over () works. I thought that Spark would
automatically treat max(instnc_id) as max(instnc_id) over ()
2. Spark tries to do max function in one task, and it runs out of memory
I’ll revert back to join. Thanks again
From: Nicholas Hakobian
Date: Friday, December 29, 2017 at 8:10 PM
To: "Lalwani, Jayesh"
Cc: "user@spark.apache.org"
Subject: Re: Subqueries
This sounds like a perfect example of using windowing functions. Have you tried
something like the following:
select ACCT_ID, CR_RVKD_STAT_CD, ACCT_SFX_NUM, SCURT_FRD_STAT_CD, CLSD_REAS_CD
from (select *, max(instnc_id) over () as max_inst_id FROM Stat_hist) where
instnc_id=max_inst_id
However, I have seen instances where window functions without partitioning
clauses will cause all partitions to be executed on one task (and spark usually
warns about this condition) and this will be very slow. It might actually be
more performant to use the inner join which, even though it is scanning through
the raw data twice, is more parallelizable.
If you have your data stored in a columnar compressed data format like parquet
or orc, the query on the right side of the join should only have a single
column, so I/O on that column would be significantly less than the full table;
you might even be able to squeeze some more performance out of it (depending on
the size of the table), by caching it beforehand.
Nicholas Szandor Hakobian, Ph.D.
Staff Data Scientist
Rally Health
nicholas.hakob...@rallyhealth.com<mailto:nicholas.hakob...@rallyhealth.com>
On Fri, Dec 29, 2017 at 1:02 PM, Lalwani, Jayesh
mailto:jayesh.lalw...@capitalone.com>> wrote:
I have a table, and I want to find the latest records in the table. The table
has a column called instnc_id that is incremented everyday. So, I want to find
the records that have the max instnc_id.
I am trying to do this using subqueries, but it gives me an error. For example,
when I try this
select ACCT_ID, CR_RVKD_STAT_CD, ACCT_SFX_NUM, SCURT_FRD_STAT_CD, CLSD_REAS_CD
from (select *, max(instnc_id) as max_inst_id FROM Stat_hist) where
instnc_id=max_inst_id
the error I get is
Caused by: org.apache.spark.sql.AnalysisException: cannot resolve
'`max_inst_id`' given input columns: [CR_RVKD_STAT_CD, ACCT_SFX_NUM,
CLSD_REAS_CD, ACCT_ID, instnc_id, SCURT_FRD_STAT_CD]; line 1 pos 172;
'Project ['ACCT_ID, 'CR_RVKD_STAT_CD, 'ACCT_SFX_NUM, 'SCURT_FRD_STAT_CD,
CLSD_REAS_CD, scalar-subquery#298 [] AS max_inst_id#299]
: +- 'Project [unresolvedalias('max('instnc_id), None)]
: +- 'UnresolvedRelation `Stat_hist`
+- 'Filter (instnc_id#92 = 'max_inst_id)
+- SubqueryAlias stat_hist
+- Project [ACCT_ID#0, ACCT_SFX_NUM#1, CR_RVKD_STAT_CD#23,
SCURT_FRD_STAT_CD#34, CLSD_REAS_CD#19, instnc_id#92]
I have tried various combinations but I keep getting into the same problem: It
doesn’t recognize max_inst_id as a column.
The only thing that works is if I get max_inst_id in a dataframe and then inner
join it with the original table
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