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From Murtadha Hubail <hubail...@gmail.com>
Subject Re: Hyracks Job Requirement Configuration
Date Mon, 29 Jan 2018 04:29:14 GMT
If reloading the data isn’t too much trouble, the first thing I would do is recreate the
instance with more partitions (e.g. partition per core or partition per 2 cores) and check
the cores utilization. If this is the same dataset as the one in your previous email, you
mentioned that it was about 10GB per partition, in that case, you might want to allocate at
least 40GB for the buffer cache and you can reduce storage.memorycomponent.globalbudget to
get enough memory to execute the job (depending on the number of partitions you create). After
recreating with higher number of partitions, don’t use “SET `compiler.parallelism` "39"”.
It will automatically use the number of partitions you create.

 

Regarding the metrics time, it includes the results printing time, so if you want to see if
it has any impact, try adding “limit 1” at the end of your query or change it to select
count(*) instead of subject_id.

 

Cheers,

Murtadha

 

From: Rana Alotaibi <ralotaib@eng.ucsd.edu>
Date: Monday, 29 January 2018 at 6:48 AM
To: <hubailmor@gmail.com>
Cc: <users@asterixdb.apache.org>, <dev@asterixdb.apache.org>
Subject: Re: Hyracks Job Requirement Configuration

 

- Do you see all cores being fully utilized during the query execution? 

 I have noticed only 6 cores were utilized
- How much time does the query take right now and how do you measure the query execution time?
Do you wait for the result to be printed somewhere (e.g. in the browser)?

I'm using the HTTP APIs. The response is a JSON object that includes the query execution time:

   { "status": "success",
        "metrics": {
                "elapsedTime": "434.627299814s",
                "executionTime": "434.626137977s",
                "resultCount": 4943,
                "resultSize": 132293,- 
                "processedObjects": 46875
        }
}

I run the query 10 times and took the average which is ~6mins.

- You mentioned that you have 4 partitions, how many physical hard drives are they mapped
to?

 One physical hard drive

- Also, increasing the sort/join memory doesn’t necessarily lead to a better performance.
Have you tried changing these values to something smaller and seeing the effects?

  Yes, I tried the following numbers:

  1) sort-memory: 32MB, join-memory: 64MB

  2) sort-memory: 64MB, join-memory: 128MB

  3) sort-memory: 128MB, join-memory:  265MB

 

The execution time remains on average ~6 - 6.5mins. I didn't see any improvement. The configurations
that I have now:

- compiler.parallelism :39 //Only 6 were utilized 

- storage.buffercache.size: 20GB

- storage.buffercache.pagesize: 1MB

 

Thanks,

Rana

On Sun, Jan 28, 2018 at 6:41 PM, Murtadha Hubail <hubailmor@gmail.com> wrote:

I have few questions if you don’t mind:

Do you see all cores being fully utilized during the query execution? 

How much time does the query take right now and how do you measure the query execution time?
Do you wait for the result to be printed somewhere (e.g. in the browser)?

You mentioned that you have 4 partitions, how many physical hard drives are they mapped to?

Also, increasing the sort/join memory doesn’t necessarily lead to a better performance.
Have you tried changing these values to something smaller and seeing the effects?

 

Cheers,

Murtadha

 

From: Rana Alotaibi <ralotaib@eng.ucsd.edu>
Date: Monday, 29 January 2018 at 5:21 AM
To: <hubailmor@gmail.com>
Cc: <users@asterixdb.apache.org>, <dev@asterixdb.apache.org>
Subject: Re: Hyracks Job Requirement Configuration

 

Thanks Murtadha! The problem solved. However, increasing the number of cores didn't help to
improve the performance of that query.

On Sun, Jan 28, 2018 at 5:05 PM, Murtadha Hubail <hubailmor@gmail.com> wrote:

Hi Rana,

The memory used for query processing is automatically calculated as follows:
JVM Max Memory - storage.buffercache.size - storage.memorycomponent.globalbudget

The documentation defaults for these parameters are outdated. The default value for storage.buffercache.size
is (JVM Max Memory / 4) and it's the same for storage.memorycomponent.globalbudget. Since
your dataset is already loaded, you could reduce the budget of storage.memorycomponent.globalbudget.
In addition, if I recall correctly, your dataset size is way smaller than what's allocated
for the buffer cache, so you might want to reduce the buffer cache budget. That should give
you more than enough memory to execute on 39 cores.

Cheers,
Murtadha


On 01/29/2018, 3:30 AM, "Mike Carey" <dtabass@gmail.com> wrote:

    + dev


    On 1/28/18 3:37 PM, Rana Alotaibi wrote:
    > Hi all,
    >
    > I would like to make AsterixDB utilizes all available CPU cores (39)
    > that I have for the following query:
    >
    > USE mimiciii;
    > SET `compiler.parallelism` "39";
    > SET `compiler.sortmemory` "128MB";
    > SET `compiler.joinmemory` "265MB";
    > SELECT P.SUBJECT_ID
    > FROM   LABITEMS I, PATIENTS P, P.ADMISSIONS A, A.LABEVENTS E
    > WHERE E.ITEMID/*+bcast*/=I.ITEMID AND
    >              E.FLAG = 'abnormal' AND
    >              I.FLUID='Blood' AND
    >              I.LABEL='Haptoglobin'
    >
    >
    > The total memory size that I have is 125GB(57GB for the AsterixDB
    > buffer cache). By running the above query, I got the following error:
    >
    > "msg": "HYR0009: Job requirement (memory: 10705403904 bytes, CPU
    > cores: 39) exceeds capacity (memory: 3258744832 bytes, CPU cores: 39)"
    >
    > How can I change this capacity default configuration? I'm looking into
    > this page : https://asterixdb.apache.org/docs/0.9.2/ncservice.html .
    > Could you please point me to the appropriate configuration parameter?
    >
    > Thanks
    > -- Rana
    >
    >
    >
    >



 

 


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