You are viewing a plain text version of this content. The canonical link for it is here.
Posted to user@predictionio.apache.org by "Guruju, Lakshmi Sravya" <la...@sap.com> on 2016/11/04 12:51:46 UTC
Not able to access engine after successful deployment
Hi,
I have setup predictionIo successfully on a linux VM. Event server is running at http://localhost:7070.
I am using elasticseacrh as data storage and it is up and running at http://localhost:9200
But when I am trying to deploy Recommendation engine, deployment was successful but I am not able to access it at localhost. You can see the below trace after successful deployment.
[WARN] [WorkflowUtils$] Non-empty parameters supplied to org.template.recommendation.Preparator, but its constructor does not accept any arguments. Stubbing with empty parameters.
[WARN] [WorkflowUtils$] Non-empty parameters supplied to org.template.recommendation.Serving, but its constructor does not accept any arguments. Stubbing with empty parameters.
[INFO] [Remoting] Starting remoting
[INFO] [Remoting] Remoting started; listening on addresses :[akka.tcp://sparkDriver@10.97.137.228:40932]
[WARN] [MetricsSystem] Using default name DAGScheduler for source because spark.app.id is not set.
[INFO] [Engine] Using persisted model
[INFO] [Engine] Custom-persisted model detected for algorithm org.template.recommendation.ALSAlgorithm
[WARN] [ALSModel] User factor does not have a partitioner. Prediction on individual records could be slow.
[WARN] [ALSModel] User factor is not cached. Prediction could be slow.
[WARN] [ALSModel] Product factor does not have a partitioner. Prediction on individual records could be slow.
[WARN] [ALSModel] Product factor is not cached. Prediction could be slow.
[INFO] [MasterActor] Undeploying any existing engine instance at http://0.0.0.0:8000
[WARN] [MasterActor] Nothing at http://0.0.0.0:8000
[INFO] [HttpListener] Bound to /0.0.0.0:8000
[INFO] [MasterActor] Engine is deployed and running. Engine API is live at http://0.0.0.0:8000.
$ curl -i -X GET "http://localhost:8000"
curl: (7) Failed to connect to localhost port 8000: Connection refused
I have also tried with different ports but nothing worked. Could someone please help me resolve these.
Regards,
Sravya
RE: Not able to access engine after successful deployment
Posted by "Guruju, Lakshmi Sravya" <la...@sap.com>.
Hi Tom,
I am able to access both event server and elasticsearch at http://localhost:7070 and https://localhost:9200 respectively. The problem is only with engine server
Also, I am able to access curl -i -X GET "http://0.0.0.0:8000" with in VM only, but I require to access it outside the VM
Regards,
Sravya
From: Tom Chan [mailto:yukhei.chan@gmail.com]
Sent: Friday, November 4, 2016 11:28 PM
To: user@predictionio.incubator.apache.org
Subject: Re: Not able to access engine after successful deployment
What do you see if you do the same call on port 7070 (and 9200)?
curl -i -X GET "http://localhost:7070<http://localhost:7070/>"
Tom
On Fri, Nov 4, 2016 at 5:55 AM, Gustavo Frederico <gu...@thinkwrap.com>> wrote:
The 0.0.0.0 IP looks a bit odd. How is your loopback network interface configured? Check with ifconfig.
On Fri, Nov 4, 2016 at 8:51 AM, Guruju, Lakshmi Sravya <la...@sap.com>> wrote:
Hi,
I have setup predictionIo successfully on a linux VM. Event server is running at http://localhost:7070.
I am using elasticseacrh as data storage and it is up and running at http://localhost:9200
But when I am trying to deploy Recommendation engine, deployment was successful but I am not able to access it at localhost. You can see the below trace after successful deployment.
[WARN] [WorkflowUtils$] Non-empty parameters supplied to org.template.recommendation.Pr<http://org.template.recommendation.Pr>eparator, but its constructor does not accept any arguments. Stubbing with empty parameters.
[WARN] [WorkflowUtils$] Non-empty parameters supplied to org.template.recommendation.Se<http://org.template.recommendation.Se>rving, but its constructor does not accept any arguments. Stubbing with empty parameters.
[INFO] [Remoting] Starting remoting
[INFO] [Remoting] Remoting started; listening on addresses :[akka.tcp://sparkDriver@10.97.137.228:40932<http://sparkDriver@10.97.137.228:40932>]
[WARN] [MetricsSystem] Using default name DAGScheduler for source because spark.app.id<http://spark.app.id> is not set.
[INFO] [Engine] Using persisted model
[INFO] [Engine] Custom-persisted model detected for algorithm org.template.recommendation.AL<http://org.template.recommendation.AL>SAlgorithm
[WARN] [ALSModel] User factor does not have a partitioner. Prediction on individual records could be slow.
[WARN] [ALSModel] User factor is not cached. Prediction could be slow.
[WARN] [ALSModel] Product factor does not have a partitioner. Prediction on individual records could be slow.
[WARN] [ALSModel] Product factor is not cached. Prediction could be slow.
[INFO] [MasterActor] Undeploying any existing engine instance at http://0.0.0.0:8000
[WARN] [MasterActor] Nothing at http://0.0.0.0:8000
[INFO] [HttpListener] Bound to /0.0.0.0:8000<http://0.0.0.0:8000>
[INFO] [MasterActor] Engine is deployed and running. Engine API is live at http://0.0.0.0:8000.
$ curl -i -X GET "http://localhost:8000"
curl: (7) Failed to connect to localhost port 8000: Connection refused
I have also tried with different ports but nothing worked. Could someone please help me resolve these.
Regards,
Sravya
Re: Not able to access engine after successful deployment
Posted by Tom Chan <yu...@gmail.com>.
What do you see if you do the same call on port 7070 (and 9200)?
curl -i -X GET "http://localhost:7070"
Tom
On Fri, Nov 4, 2016 at 5:55 AM, Gustavo Frederico <
gustavo.frederico@thinkwrap.com> wrote:
> The 0.0.0.0 IP looks a bit odd. How is your loopback network interface
> configured? Check with ifconfig.
>
> On Fri, Nov 4, 2016 at 8:51 AM, Guruju, Lakshmi Sravya <
> lakshmi.sravya.guruju@sap.com> wrote:
>
>> Hi,
>>
>>
>>
>> I have setup predictionIo successfully on a linux VM. Event server is
>> running at http://localhost:7070.
>>
>>
>>
>> I am using elasticseacrh as data storage and it is up and running at
>> http://localhost:9200
>>
>>
>>
>> But when I am trying to deploy Recommendation engine, deployment was
>> successful but I am not able to access it at localhost. You can see the
>> below trace after successful deployment.
>>
>>
>>
>> [WARN] [WorkflowUtils$] Non-empty parameters supplied to
>> org.template.recommendation.Preparator, but its constructor does not
>> accept any arguments. Stubbing with empty parameters.
>>
>> [WARN] [WorkflowUtils$] Non-empty parameters supplied to
>> org.template.recommendation.Serving, but its constructor does not accept
>> any arguments. Stubbing with empty parameters.
>>
>> [INFO] [Remoting] Starting remoting
>>
>> [INFO] [Remoting] Remoting started; listening on addresses :[akka.tcp://
>> sparkDriver@10.97.137.228:40932]
>>
>> [WARN] [MetricsSystem] Using default name DAGScheduler for source because
>> spark.app.id is not set.
>>
>> [INFO] [Engine] Using persisted model
>>
>> [INFO] [Engine] Custom-persisted model detected for algorithm
>> org.template.recommendation.ALSAlgorithm
>>
>> [WARN] [ALSModel] User factor does not have a partitioner. Prediction on
>> individual records could be slow.
>>
>> [WARN] [ALSModel] User factor is not cached. Prediction could be slow.
>>
>> [WARN] [ALSModel] Product factor does not have a partitioner. Prediction
>> on individual records could be slow.
>>
>> [WARN] [ALSModel] Product factor is not cached. Prediction could be slow.
>>
>> [INFO] [MasterActor] Undeploying any existing engine instance at
>> http://0.0.0.0:8000
>>
>> [WARN] [MasterActor] Nothing at http://0.0.0.0:8000
>>
>> [INFO] [HttpListener] Bound to /0.0.0.0:8000
>>
>> [INFO] [MasterActor] Engine is deployed and running. Engine API is live
>> at http://0.0.0.0:8000.
>>
>>
>>
>>
>>
>> $ curl -i -X GET "http://localhost:8000"
>>
>> curl: (7) Failed to connect to localhost port 8000: Connection refused
>>
>>
>>
>> I have also tried with different ports but nothing worked. Could someone
>> please help me resolve these.
>>
>>
>>
>> Regards,
>>
>> Sravya
>>
>
>
RE: Not able to access engine after successful deployment
Posted by Tom Chan <yu...@gmail.com>.
I'd search for "virtualbox port forwarding" (say you're using virtualbox)
for details of how to set it up.
Tom
On Nov 5, 2016 12:32 AM, "Guruju, Lakshmi Sravya" <
lakshmi.sravya.guruju@sap.com> wrote:
>
> Hi Tom,
>
>
>
> You are right. Port seems to be closed. When I try nmap to display open
ports, I got below result. At this moment the engine is deployed but still
8000 port is not open. How can I make it open so that I can access it
outside the VM.
>
>
>
> Nmap scan report for localhost (127.0.0.1)
>
> Not shown: 996 closed ports
>
> PORT STATE SERVICE
>
> 22/tcp open ssh
>
> 5432/tcp open postgresql
>
> 7070/tcp open realserver
>
> 9200/tcp open wap-wsp
>
>
>
> Regards,
>
> Sravya
*>*
*> From:* Tom Chan [mailto:yukhei.chan@gmail.com]
*> Sent:* Saturday, November 5, 2016 12:25 AM
>
*> To:* user@predictionio.incubator.apache.org
*> Subject:* Re: Not able to access engine after successful deployment
>
>
>
> Seems you need to set up your VM so that traffic arriving at a certain
port on your host (8000 or something of your choice) is forwarded to port
8000 on your VM, then you're good to go.
>
>
>
> Tom
>
>
>
> On Fri, Nov 4, 2016 at 11:48 AM, Guruju, Lakshmi Sravya <
lakshmi.sravya.guruju@sap.com> wrote:
>>
>> Hi,
>>
>>
>>
>> It is configured to 127.0.0.1
>>
>>
>>
>> Link encap:Local Loopback
>>
>> inet addr:127.0.0.1 Mask:255.0.0.0
>>
>>
>>
>> Regards,
>>
>> Sravya
>>
>>
*>>*
*>> From:* Gustavo Frederico [mailto:gustavo.frederico@thinkwrap.com]
*>> Sent:* Friday, November 4, 2016 6:25 PM
*>> To:* user@predictionio.incubator.apache.org
*>> Subject:* Re: Not able to access engine after successful deployment
>>
>>
>>
>> The 0.0.0.0 IP looks a bit odd. How is your loopback network interface
configured? Check with ifconfig.
>>
>>
>>
>> On Fri, Nov 4, 2016 at 8:51 AM, Guruju, Lakshmi Sravya <
lakshmi.sravya.guruju@sap.com> wrote:
>>>
>>> Hi,
>>>
>>>
>>>
>>> I have setup predictionIo successfully on a linux VM. Event server is
running at http://localhost:7070.
>>>
>>>
>>>
>>> I am using elasticseacrh as data storage and it is up and running at
http://localhost:9200
>>>
>>>
>>>
>>> But when I am trying to deploy Recommendation engine, deployment was
successful but I am not able to access it at localhost. You can see the
below trace after successful deployment.
>>>
>>>
>>>
>>> [WARN] [WorkflowUtils$] Non-empty parameters supplied to
org.template.recommendation.Preparator, but its constructor does not accept
any arguments. Stubbing with empty parameters.
>>>
>>> [WARN] [WorkflowUtils$] Non-empty parameters supplied to
org.template.recommendation.Serving, but its constructor does not accept
any arguments. Stubbing with empty parameters.
>>>
>>> [INFO] [Remoting] Starting remoting
>>>
>>> [INFO] [Remoting] Remoting started; listening on addresses :[akka.tcp://
sparkDriver@10.97.137.228:40932]
>>>
>>> [WARN] [MetricsSystem] Using default name DAGScheduler for source
because spark.app.id is not set.
>>>
>>> [INFO] [Engine] Using persisted model
>>>
>>> [INFO] [Engine] Custom-persisted model detected for algorithm
org.template.recommendation.ALSAlgorithm
>>>
>>> [WARN] [ALSModel] User factor does not have a partitioner. Prediction
on individual records could be slow.
>>>
>>> [WARN] [ALSModel] User factor is not cached. Prediction could be slow.
>>>
>>> [WARN] [ALSModel] Product factor does not have a partitioner.
Prediction on individual records could be slow.
>>>
>>> [WARN] [ALSModel] Product factor is not cached. Prediction could be
slow.
>>>
>>> [INFO] [MasterActor] Undeploying any existing engine instance at
http://0.0.0.0:8000
>>>
>>> [WARN] [MasterActor] Nothing at http://0.0.0.0:8000
>>>
>>> [INFO] [HttpListener] Bound to /0.0.0.0:8000
>>>
>>> [INFO] [MasterActor] Engine is deployed and running. Engine API is live
at http://0.0.0.0:8000.
>>>
>>>
>>>
>>>
>>>
>>> $ curl -i -X GET "http://localhost:8000"
>>>
>>> curl: (7) Failed to connect to localhost port 8000: Connection refused
>>>
>>>
>>>
>>> I have also tried with different ports but nothing worked. Could
someone please help me resolve these.
>>>
>>>
>>>
>>> Regards,
>>>
>>> Sravya
>>
>>
>
>
RE: Not able to access engine after successful deployment
Posted by "Guruju, Lakshmi Sravya" <la...@sap.com>.
Hi Tom,
You are right. Port seems to be closed. When I try nmap to display open ports, I got below result. At this moment the engine is deployed but still 8000 port is not open. How can I make it open so that I can access it outside the VM.
Nmap scan report for localhost (127.0.0.1)
Not shown: 996 closed ports
PORT STATE SERVICE
22/tcp open ssh
5432/tcp open postgresql
7070/tcp open realserver
9200/tcp open wap-wsp
Regards,
Sravya
From: Tom Chan [mailto:yukhei.chan@gmail.com]
Sent: Saturday, November 5, 2016 12:25 AM
To: user@predictionio.incubator.apache.org
Subject: Re: Not able to access engine after successful deployment
Seems you need to set up your VM so that traffic arriving at a certain port on your host (8000 or something of your choice) is forwarded to port 8000 on your VM, then you're good to go.
Tom
On Fri, Nov 4, 2016 at 11:48 AM, Guruju, Lakshmi Sravya <la...@sap.com>> wrote:
Hi,
It is configured to 127.0.0.1
Link encap:Local Loopback
inet addr:127.0.0.1 Mask:255.0.0.0
Regards,
Sravya
From: Gustavo Frederico [mailto:gustavo.frederico@thinkwrap.com<ma...@thinkwrap.com>]
Sent: Friday, November 4, 2016 6:25 PM
To: user@predictionio.incubator.apache.org<ma...@predictionio.incubator.apache.org>
Subject: Re: Not able to access engine after successful deployment
The 0.0.0.0 IP looks a bit odd. How is your loopback network interface configured? Check with ifconfig.
On Fri, Nov 4, 2016 at 8:51 AM, Guruju, Lakshmi Sravya <la...@sap.com>> wrote:
Hi,
I have setup predictionIo successfully on a linux VM. Event server is running at http://localhost:7070.
I am using elasticseacrh as data storage and it is up and running at http://localhost:9200
But when I am trying to deploy Recommendation engine, deployment was successful but I am not able to access it at localhost. You can see the below trace after successful deployment.
[WARN] [WorkflowUtils$] Non-empty parameters supplied to org.template.recommendation.Preparator, but its constructor does not accept any arguments. Stubbing with empty parameters.
[WARN] [WorkflowUtils$] Non-empty parameters supplied to org.template.recommendation.Serving, but its constructor does not accept any arguments. Stubbing with empty parameters.
[INFO] [Remoting] Starting remoting
[INFO] [Remoting] Remoting started; listening on addresses :[akka.tcp://sparkDriver@10.97.137.228:40932<http://sparkDriver@10.97.137.228:40932>]
[WARN] [MetricsSystem] Using default name DAGScheduler for source because spark.app.id<http://spark.app.id> is not set.
[INFO] [Engine] Using persisted model
[INFO] [Engine] Custom-persisted model detected for algorithm org.template.recommendation.ALSAlgorithm
[WARN] [ALSModel] User factor does not have a partitioner. Prediction on individual records could be slow.
[WARN] [ALSModel] User factor is not cached. Prediction could be slow.
[WARN] [ALSModel] Product factor does not have a partitioner. Prediction on individual records could be slow.
[WARN] [ALSModel] Product factor is not cached. Prediction could be slow.
[INFO] [MasterActor] Undeploying any existing engine instance at http://0.0.0.0:8000
[WARN] [MasterActor] Nothing at http://0.0.0.0:8000
[INFO] [HttpListener] Bound to /0.0.0.0:8000<http://0.0.0.0:8000>
[INFO] [MasterActor] Engine is deployed and running. Engine API is live at http://0.0.0.0:8000.
$ curl -i -X GET "http://localhost:8000"
curl: (7) Failed to connect to localhost port 8000: Connection refused
I have also tried with different ports but nothing worked. Could someone please help me resolve these.
Regards,
Sravya
Re: Not able to access engine after successful deployment
Posted by Tom Chan <yu...@gmail.com>.
Seems you need to set up your VM so that traffic arriving at a certain port
on your host (8000 or something of your choice) is forwarded to port 8000
on your VM, then you're good to go.
Tom
On Fri, Nov 4, 2016 at 11:48 AM, Guruju, Lakshmi Sravya <
lakshmi.sravya.guruju@sap.com> wrote:
> Hi,
>
>
>
> It is configured to 127.0.0.1
>
>
>
> Link encap:Local Loopback
>
> inet addr:127.0.0.1 Mask:255.0.0.0
>
>
>
> Regards,
>
> Sravya
>
>
>
> *From:* Gustavo Frederico [mailto:gustavo.frederico@thinkwrap.com]
> *Sent:* Friday, November 4, 2016 6:25 PM
> *To:* user@predictionio.incubator.apache.org
> *Subject:* Re: Not able to access engine after successful deployment
>
>
>
> The 0.0.0.0 IP looks a bit odd. How is your loopback network interface
> configured? Check with ifconfig.
>
>
>
> On Fri, Nov 4, 2016 at 8:51 AM, Guruju, Lakshmi Sravya <
> lakshmi.sravya.guruju@sap.com> wrote:
>
> Hi,
>
>
>
> I have setup predictionIo successfully on a linux VM. Event server is
> running at http://localhost:7070.
>
>
>
> I am using elasticseacrh as data storage and it is up and running at
> http://localhost:9200
>
>
>
> But when I am trying to deploy Recommendation engine, deployment was
> successful but I am not able to access it at localhost. You can see the
> below trace after successful deployment.
>
>
>
> [WARN] [WorkflowUtils$] Non-empty parameters supplied to
> org.template.recommendation.Preparator, but its constructor does not
> accept any arguments. Stubbing with empty parameters.
>
> [WARN] [WorkflowUtils$] Non-empty parameters supplied to
> org.template.recommendation.Serving, but its constructor does not accept
> any arguments. Stubbing with empty parameters.
>
> [INFO] [Remoting] Starting remoting
>
> [INFO] [Remoting] Remoting started; listening on addresses :[akka.tcp://
> sparkDriver@10.97.137.228:40932]
>
> [WARN] [MetricsSystem] Using default name DAGScheduler for source because
> spark.app.id is not set.
>
> [INFO] [Engine] Using persisted model
>
> [INFO] [Engine] Custom-persisted model detected for algorithm
> org.template.recommendation.ALSAlgorithm
>
> [WARN] [ALSModel] User factor does not have a partitioner. Prediction on
> individual records could be slow.
>
> [WARN] [ALSModel] User factor is not cached. Prediction could be slow.
>
> [WARN] [ALSModel] Product factor does not have a partitioner. Prediction
> on individual records could be slow.
>
> [WARN] [ALSModel] Product factor is not cached. Prediction could be slow.
>
> [INFO] [MasterActor] Undeploying any existing engine instance at
> http://0.0.0.0:8000
>
> [WARN] [MasterActor] Nothing at http://0.0.0.0:8000
>
> [INFO] [HttpListener] Bound to /0.0.0.0:8000
>
> [INFO] [MasterActor] Engine is deployed and running. Engine API is live at
> http://0.0.0.0:8000.
>
>
>
>
>
> $ curl -i -X GET "http://localhost:8000"
>
> curl: (7) Failed to connect to localhost port 8000: Connection refused
>
>
>
> I have also tried with different ports but nothing worked. Could someone
> please help me resolve these.
>
>
>
> Regards,
>
> Sravya
>
>
>
RE: Not able to access engine after successful deployment
Posted by "Guruju, Lakshmi Sravya" <la...@sap.com>.
Hi,
It is configured to 127.0.0.1
Link encap:Local Loopback
inet addr:127.0.0.1 Mask:255.0.0.0
Regards,
Sravya
From: Gustavo Frederico [mailto:gustavo.frederico@thinkwrap.com]
Sent: Friday, November 4, 2016 6:25 PM
To: user@predictionio.incubator.apache.org
Subject: Re: Not able to access engine after successful deployment
The 0.0.0.0 IP looks a bit odd. How is your loopback network interface configured? Check with ifconfig.
On Fri, Nov 4, 2016 at 8:51 AM, Guruju, Lakshmi Sravya <la...@sap.com>> wrote:
Hi,
I have setup predictionIo successfully on a linux VM. Event server is running at http://localhost:7070.
I am using elasticseacrh as data storage and it is up and running at http://localhost:9200
But when I am trying to deploy Recommendation engine, deployment was successful but I am not able to access it at localhost. You can see the below trace after successful deployment.
[WARN] [WorkflowUtils$] Non-empty parameters supplied to org.template.recommendation.Preparator, but its constructor does not accept any arguments. Stubbing with empty parameters.
[WARN] [WorkflowUtils$] Non-empty parameters supplied to org.template.recommendation.Serving, but its constructor does not accept any arguments. Stubbing with empty parameters.
[INFO] [Remoting] Starting remoting
[INFO] [Remoting] Remoting started; listening on addresses :[akka.tcp://sparkDriver@10.97.137.228:40932<http://sparkDriver@10.97.137.228:40932>]
[WARN] [MetricsSystem] Using default name DAGScheduler for source because spark.app.id<http://spark.app.id> is not set.
[INFO] [Engine] Using persisted model
[INFO] [Engine] Custom-persisted model detected for algorithm org.template.recommendation.ALSAlgorithm
[WARN] [ALSModel] User factor does not have a partitioner. Prediction on individual records could be slow.
[WARN] [ALSModel] User factor is not cached. Prediction could be slow.
[WARN] [ALSModel] Product factor does not have a partitioner. Prediction on individual records could be slow.
[WARN] [ALSModel] Product factor is not cached. Prediction could be slow.
[INFO] [MasterActor] Undeploying any existing engine instance at http://0.0.0.0:8000
[WARN] [MasterActor] Nothing at http://0.0.0.0:8000
[INFO] [HttpListener] Bound to /0.0.0.0:8000<http://0.0.0.0:8000>
[INFO] [MasterActor] Engine is deployed and running. Engine API is live at http://0.0.0.0:8000.
$ curl -i -X GET "http://localhost:8000"
curl: (7) Failed to connect to localhost port 8000: Connection refused
I have also tried with different ports but nothing worked. Could someone please help me resolve these.
Regards,
Sravya
Re: Not able to access engine after successful deployment
Posted by Gustavo Frederico <gu...@thinkwrap.com>.
The 0.0.0.0 IP looks a bit odd. How is your loopback network interface
configured? Check with ifconfig.
On Fri, Nov 4, 2016 at 8:51 AM, Guruju, Lakshmi Sravya <
lakshmi.sravya.guruju@sap.com> wrote:
> Hi,
>
>
>
> I have setup predictionIo successfully on a linux VM. Event server is
> running at http://localhost:7070.
>
>
>
> I am using elasticseacrh as data storage and it is up and running at
> http://localhost:9200
>
>
>
> But when I am trying to deploy Recommendation engine, deployment was
> successful but I am not able to access it at localhost. You can see the
> below trace after successful deployment.
>
>
>
> [WARN] [WorkflowUtils$] Non-empty parameters supplied to
> org.template.recommendation.Preparator, but its constructor does not
> accept any arguments. Stubbing with empty parameters.
>
> [WARN] [WorkflowUtils$] Non-empty parameters supplied to
> org.template.recommendation.Serving, but its constructor does not accept
> any arguments. Stubbing with empty parameters.
>
> [INFO] [Remoting] Starting remoting
>
> [INFO] [Remoting] Remoting started; listening on addresses :[akka.tcp://
> sparkDriver@10.97.137.228:40932]
>
> [WARN] [MetricsSystem] Using default name DAGScheduler for source because
> spark.app.id is not set.
>
> [INFO] [Engine] Using persisted model
>
> [INFO] [Engine] Custom-persisted model detected for algorithm
> org.template.recommendation.ALSAlgorithm
>
> [WARN] [ALSModel] User factor does not have a partitioner. Prediction on
> individual records could be slow.
>
> [WARN] [ALSModel] User factor is not cached. Prediction could be slow.
>
> [WARN] [ALSModel] Product factor does not have a partitioner. Prediction
> on individual records could be slow.
>
> [WARN] [ALSModel] Product factor is not cached. Prediction could be slow.
>
> [INFO] [MasterActor] Undeploying any existing engine instance at
> http://0.0.0.0:8000
>
> [WARN] [MasterActor] Nothing at http://0.0.0.0:8000
>
> [INFO] [HttpListener] Bound to /0.0.0.0:8000
>
> [INFO] [MasterActor] Engine is deployed and running. Engine API is live at
> http://0.0.0.0:8000.
>
>
>
>
>
> $ curl -i -X GET "http://localhost:8000"
>
> curl: (7) Failed to connect to localhost port 8000: Connection refused
>
>
>
> I have also tried with different ports but nothing worked. Could someone
> please help me resolve these.
>
>
>
> Regards,
>
> Sravya
>