Michael what exactly do you mean by "flattened" version/structure here e.g.:

1. An Object with only primitive data types as attributes
2. An Object with  no more than one level of other Objects as attributes 
3. An Array/List of primitive types 
4. An Array/List of Objects 

This question is in general about RDDs not necessarily RDDs in the context of 
SparkSQL

When answering can you also score how bad the performance of each of the above 
options is  

-----Original Message-----
From: Christian Perez [mailto:christ...@svds.com] 
Sent: Thursday, April 16, 2015 6:09 PM
To: Michael Armbrust
Cc: user
Subject: Re: Super slow caching in 1.3?

Hi Michael,

Good question! We checked 1.2 and found that it is also slow cacheing the same 
flat parquet file. Caching other file formats of the same data were faster by 
up to a factor of ~2. Note that the parquet file was created in Impala but the 
other formats were written by Spark SQL.

Cheers,

Christian

On Mon, Apr 6, 2015 at 6:17 PM, Michael Armbrust <mich...@databricks.com> wrote:
> Do you think you are seeing a regression from 1.2?  Also, are you 
> caching nested data or flat rows?  The in-memory caching is not really 
> designed for nested data and so performs pretty slowly here (its just 
> falling back to kryo and even then there are some locking issues).
>
> If so, would it be possible to try caching a flattened version?
>
> CACHE TABLE flattenedTable AS SELECT ... FROM parquetTable
>
> On Mon, Apr 6, 2015 at 5:00 PM, Christian Perez <christ...@svds.com> wrote:
>>
>> Hi all,
>>
>> Has anyone else noticed very slow time to cache a Parquet file? It 
>> takes 14 s per 235 MB (1 block) uncompressed node local Parquet file 
>> on M2 EC2 instances. Or are my expectations way off...
>>
>> Cheers,
>>
>> Christian
>>
>> --
>> Christian Perez
>> Silicon Valley Data Science
>> Data Analyst
>> christ...@svds.com
>> @cp_phd
>>
>> ---------------------------------------------------------------------
>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For 
>> additional commands, e-mail: user-h...@spark.apache.org
>>
>



--
Christian Perez
Silicon Valley Data Science
Data Analyst
christ...@svds.com
@cp_phd

---------------------------------------------------------------------
To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional 
commands, e-mail: user-h...@spark.apache.org



---------------------------------------------------------------------
To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
For additional commands, e-mail: user-h...@spark.apache.org

Reply via email to