The patch is here https://github.com/apache/incubator-predictionio/pull/367

On Thursday, April 6, 2017 at 8:13:31 PM UTC+3, juha.s...@gmail.com wrote:
>
> I'll try make a patch for this to PredicitionIO during the weekend if I 
> have the time.
>
> On Thursday, April 6, 2017 at 8:07:31 PM UTC+3, pat wrote:
>>
>> Hmm, interesting. I have heard of this being a problem in PredictionIO 
>> but haven’t heard this explanation before IIRC.
>>
>>
>> On Apr 6, 2017, at 9:47 AM, juha.s...@gmail.com wrote:
>>
>> Ah, I just found the problem: a fresh AWS instance takes a long time to 
>> generate enough entropy so that a random access key can be generated. 
>>
>> Related github issue: 
>> https://github.com/apache/incubator-predictionio/issues/253
>>
>> More discussion about the a similar problem: 
>> https://groups.google.com/forum/#!searchin/actionml-user/aws%7Csort:relevance/actionml-user/N9o2jBkyF_w/bUYr5U8zFQAJ
>>
>>
>> On Thursday, April 6, 2017 at 7:33:49 PM UTC+3, juha.s...@gmail.com 
>> wrote:
>>>
>>> Hi,
>>>
>>> Yes, it is clear that the AWS image is for dev only. I was just 
>>> wondering the slowness of the a newly created instance when it has no data. 
>>>
>>> However can't be that the HDFS is out of space. I ran those commands 
>>> right after creating a new AWS instance. I don't have any engines running 
>>> or configured, and I have not added any data yet to the system. The machine 
>>> seems to be completely idle while adding the new application.
>>>
>>> Current HDFS usage:
>>>
>>> $ ./hadoop fs -df -h
>>>
>>> Filesystem              Size   Used  Available  Use%
>>>
>>> hdfs://127.0.0.1:9000  7.7 G  220 K      1.9 G    0%
>>>
>>> Also system has plenty of free memory
>>>
>>> $ free -h
>>>
>>>               total        used        free      shared  buff/cache   
>>> available
>>>
>>> Mem:            14G        2.0G         12G        8.6M        404M     
>>>     12G
>>>
>>> Swap:            0B          0B          0B
>>>
>>>
>>>
>>> On Thursday, April 6, 2017 at 6:47:53 PM UTC+3, pat wrote:
>>>>
>>>> Yes, this is sometimes true and it could be a couple things. Some 
>>>> operations in HDFS are slow to complete since they require replication. 
>>>> Even starting a cluster can take minutes. Is it a problem? Is it possible 
>>>> HBase is getting full (check remaining data in HDFS). or needs to be 
>>>> scaled? The all-in-one instance on AWS only uses vertical scaling by 
>>>> number 
>>>> of cores, amount of memory, and disk space since all services run on one 
>>>> machine. You can “stop” the instance and change the type to a larger 
>>>> instance then “start” it to get it scaled. You have to snapshot the disk 
>>>> to 
>>>> scale disk by copying to a new one and attaching the new volume.
>>>>
>>>> I hope it was clear that the AWS AMI was meant for dev, not production.
>>>>
>>>> On Apr 6, 2017, at 6:12 AM, juha.s...@gmail.com wrote:
>>>>
>>>> Hi,
>>>>
>>>> I am using ready-made AWS image from 
>>>> http://actionml.com/docs/awssetupguide with r3.large instance in 
>>>> eu-central-1 region.
>>>>
>>>> I followed installation instructions to the letter. Integration test 
>>>> passes but takes many minutes. Probably because creating a new a new app 
>>>> takes so long.
>>>>
>>>> Then I tried creating a new application and that takes about 10 
>>>> minutes. Is this normal? 
>>>>
>>>> What this command is actually doing? I had assumed that it would just 
>>>> create few records to the databases, which should take just a dozen 
>>>> seconds 
>>>> or so.
>>>>
>>>> Here is a log for creating a new application. Most of the time is spent 
>>>> lines 'HBLEvents' and '[App$] Initialized Event...'
>>>>
>>>> $ time pio app new foobar123
>>>> [INFO] [HBLEvents] The table pio_event:events_3 doesn't exist yet. 
>>>> Creating now...
>>>> [INFO] [App$] Initialized Event Store for this app ID: 3.
>>>> [INFO] [App$] Created new app:
>>>> [INFO] [App$]       Name: foobar123
>>>> [INFO] [App$]         ID: 3
>>>> [INFO] [App$] Access Key: ....
>>>>
>>>> real 9m58.891s
>>>> user 0m9.632s
>>>> sys 0m0.352s
>>>>
>>>>
>>>> -- 
>>>> Juha Syrjälä
>>>>
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