Re: spark streaming with kinesis

[Takeshi Yamamuro]

"1 userid data" is ambiguous though (user-input data? stream? shard?),
since a kinesis worker fetch data from shards that the worker has an
ownership of, IIUC user-input data in a shard are transferred into an
assigned worker as long as you get no failure.

// maropu

On Mon, Nov 21, 2016 at 1:59 PM, Shushant Arora 
wrote:

> Hi
>
> Thanks.
> Have a doubt on spark streaming kinesis consumer. Say I have a batch time
> of 500 ms and kiensis stream is partitioned on userid(uniformly
> distributed).But since IdleTimeBetweenReadsInMillis is set to 1000ms so
> Spark receiver nodes will fetch the data at interval of 1 second and store
> in InputDstream.
>
> 1. When worker executors will fetch the data from receiver at after every
> 500 ms does its gurantee that 1 userid data will go to one partition and
> that to one worker only always ?
> 2.If not - can I repartition stream data before processing? If yes how-
> since JavaDStream has only one method repartition which takes number of
> partitions and not the partitioner function ?So it will randomly
> repartition the Dstream data.
>
> Thanks
>
>
>
>
>
>
>
>
> On Tue, Nov 15, 2016 at 8:23 AM, Takeshi Yamamuro 
> wrote:
>
>> Seems it it not a good design to frequently restart workers in a minute
>> because
>> their initialization and shutdown take much time as you said
>> (e.g., interconnection overheads with dynamodb and graceful shutdown).
>>
>> Anyway, since this is a kind of questions about the aws kinesis library,
>> so
>> you'd better to ask aws guys in their forum or something.
>>
>> // maropu
>>
>>
>> On Mon, Nov 14, 2016 at 11:20 PM, Shushant Arora <
>> shushantaror...@gmail.com> wrote:
>>
>>> 1.No, I want to implement low level consumer on kinesis stream.
>>> so need to stop the worker once it read the latest sequence number sent
>>> by driver.
>>>
>>> 2.What is the cost of frequent register and deregister of worker node.
>>> Is that when worker's shutdown is called it will terminate run method but
>>> leasecoordinator will wait for 2seconds before releasing the lease. So I
>>> cannot deregister a worker in less than 2 seconds ?
>>>
>>> Thanks!
>>>
>>>
>>>
>>> On Mon, Nov 14, 2016 at 7:36 PM, Takeshi Yamamuro >> > wrote:
>>>
 Is "aws kinesis get-shard-iterator --shard-iterator-type LATEST" not
 enough for your usecase?

 On Mon, Nov 14, 2016 at 10:23 PM, Shushant Arora <
 shushantaror...@gmail.com> wrote:

> Thanks!
> Is there a way to get the latest sequence number of all shards of a
> kinesis stream?
>
>
>
> On Mon, Nov 14, 2016 at 5:43 PM, Takeshi Yamamuro <
> linguin@gmail.com> wrote:
>
>> Hi,
>>
>> The time interval can be controlled by `IdleTimeBetweenReadsInMillis`
>> in KinesisClientLibConfiguration though,
>> it is not configurable in the current implementation.
>>
>> The detail can be found in;
>> https://github.com/apache/spark/blob/master/external/kinesis
>> -asl/src/main/scala/org/apache/spark/streaming/kinesis/Kines
>> isReceiver.scala#L152
>>
>> // maropu
>>
>>
>> On Sun, Nov 13, 2016 at 12:08 AM, Shushant Arora <
>> shushantaror...@gmail.com> wrote:
>>
>>> *Hi *
>>>
>>> *is **spark.streaming.blockInterval* for kinesis input stream is
>>> hardcoded to 1 sec or is it configurable ? Time interval at which 
>>> receiver
>>> fetched data from kinesis .
>>>
>>> Means stream batch interval cannot be less than 
>>> *spark.streaming.blockInterval
>>> and this should be configrable , Also is there any minimum value for
>>> streaming batch interval ?*
>>>
>>> *Thanks*
>>>
>>>
>>
>>
>> --
>> ---
>> Takeshi Yamamuro
>>
>
>


 --
 ---
 Takeshi Yamamuro

>>>
>>>
>>
>>
>> --
>> ---
>> Takeshi Yamamuro
>>
>
>


-- 
---
Takeshi Yamamuro

Re: spark streaming with kinesis

[Shushant Arora]

Hi

Thanks.
Have a doubt on spark streaming kinesis consumer. Say I have a batch time
of 500 ms and kiensis stream is partitioned on userid(uniformly
distributed).But since IdleTimeBetweenReadsInMillis is set to 1000ms so
Spark receiver nodes will fetch the data at interval of 1 second and store
in InputDstream.

1. When worker executors will fetch the data from receiver at after every
500 ms does its gurantee that 1 userid data will go to one partition and
that to one worker only always ?
2.If not - can I repartition stream data before processing? If yes how-
since JavaDStream has only one method repartition which takes number of
partitions and not the partitioner function ?So it will randomly
repartition the Dstream data.

Thanks








On Tue, Nov 15, 2016 at 8:23 AM, Takeshi Yamamuro 
wrote:

> Seems it it not a good design to frequently restart workers in a minute
> because
> their initialization and shutdown take much time as you said
> (e.g., interconnection overheads with dynamodb and graceful shutdown).
>
> Anyway, since this is a kind of questions about the aws kinesis library, so
> you'd better to ask aws guys in their forum or something.
>
> // maropu
>
>
> On Mon, Nov 14, 2016 at 11:20 PM, Shushant Arora <
> shushantaror...@gmail.com> wrote:
>
>> 1.No, I want to implement low level consumer on kinesis stream.
>> so need to stop the worker once it read the latest sequence number sent
>> by driver.
>>
>> 2.What is the cost of frequent register and deregister of worker node. Is
>> that when worker's shutdown is called it will terminate run method but
>> leasecoordinator will wait for 2seconds before releasing the lease. So I
>> cannot deregister a worker in less than 2 seconds ?
>>
>> Thanks!
>>
>>
>>
>> On Mon, Nov 14, 2016 at 7:36 PM, Takeshi Yamamuro 
>> wrote:
>>
>>> Is "aws kinesis get-shard-iterator --shard-iterator-type LATEST" not
>>> enough for your usecase?
>>>
>>> On Mon, Nov 14, 2016 at 10:23 PM, Shushant Arora <
>>> shushantaror...@gmail.com> wrote:
>>>
 Thanks!
 Is there a way to get the latest sequence number of all shards of a
 kinesis stream?



 On Mon, Nov 14, 2016 at 5:43 PM, Takeshi Yamamuro <
 linguin@gmail.com> wrote:

> Hi,
>
> The time interval can be controlled by `IdleTimeBetweenReadsInMillis`
> in KinesisClientLibConfiguration though,
> it is not configurable in the current implementation.
>
> The detail can be found in;
> https://github.com/apache/spark/blob/master/external/kinesis
> -asl/src/main/scala/org/apache/spark/streaming/kinesis/Kines
> isReceiver.scala#L152
>
> // maropu
>
>
> On Sun, Nov 13, 2016 at 12:08 AM, Shushant Arora <
> shushantaror...@gmail.com> wrote:
>
>> *Hi *
>>
>> *is **spark.streaming.blockInterval* for kinesis input stream is
>> hardcoded to 1 sec or is it configurable ? Time interval at which 
>> receiver
>> fetched data from kinesis .
>>
>> Means stream batch interval cannot be less than 
>> *spark.streaming.blockInterval
>> and this should be configrable , Also is there any minimum value for
>> streaming batch interval ?*
>>
>> *Thanks*
>>
>>
>
>
> --
> ---
> Takeshi Yamamuro
>


>>>
>>>
>>> --
>>> ---
>>> Takeshi Yamamuro
>>>
>>
>>
>
>
> --
> ---
> Takeshi Yamamuro
>

Re: spark streaming with kinesis

[Takeshi Yamamuro]

Seems it it not a good design to frequently restart workers in a minute
because
their initialization and shutdown take much time as you said
(e.g., interconnection overheads with dynamodb and graceful shutdown).

Anyway, since this is a kind of questions about the aws kinesis library, so
you'd better to ask aws guys in their forum or something.

// maropu


On Mon, Nov 14, 2016 at 11:20 PM, Shushant Arora 
wrote:

> 1.No, I want to implement low level consumer on kinesis stream.
> so need to stop the worker once it read the latest sequence number sent by
> driver.
>
> 2.What is the cost of frequent register and deregister of worker node. Is
> that when worker's shutdown is called it will terminate run method but
> leasecoordinator will wait for 2seconds before releasing the lease. So I
> cannot deregister a worker in less than 2 seconds ?
>
> Thanks!
>
>
>
> On Mon, Nov 14, 2016 at 7:36 PM, Takeshi Yamamuro 
> wrote:
>
>> Is "aws kinesis get-shard-iterator --shard-iterator-type LATEST" not
>> enough for your usecase?
>>
>> On Mon, Nov 14, 2016 at 10:23 PM, Shushant Arora <
>> shushantaror...@gmail.com> wrote:
>>
>>> Thanks!
>>> Is there a way to get the latest sequence number of all shards of a
>>> kinesis stream?
>>>
>>>
>>>
>>> On Mon, Nov 14, 2016 at 5:43 PM, Takeshi Yamamuro >> > wrote:
>>>
 Hi,

 The time interval can be controlled by `IdleTimeBetweenReadsInMillis`
 in KinesisClientLibConfiguration though,
 it is not configurable in the current implementation.

 The detail can be found in;
 https://github.com/apache/spark/blob/master/external/kinesis
 -asl/src/main/scala/org/apache/spark/streaming/kinesis/Kines
 isReceiver.scala#L152

 // maropu


 On Sun, Nov 13, 2016 at 12:08 AM, Shushant Arora <
 shushantaror...@gmail.com> wrote:

> *Hi *
>
> *is **spark.streaming.blockInterval* for kinesis input stream is
> hardcoded to 1 sec or is it configurable ? Time interval at which receiver
> fetched data from kinesis .
>
> Means stream batch interval cannot be less than 
> *spark.streaming.blockInterval
> and this should be configrable , Also is there any minimum value for
> streaming batch interval ?*
>
> *Thanks*
>
>


 --
 ---
 Takeshi Yamamuro

>>>
>>>
>>
>>
>> --
>> ---
>> Takeshi Yamamuro
>>
>
>


-- 
---
Takeshi Yamamuro

Re: spark streaming with kinesis

[Shushant Arora]

1.No, I want to implement low level consumer on kinesis stream.
so need to stop the worker once it read the latest sequence number sent by
driver.

2.What is the cost of frequent register and deregister of worker node. Is
that when worker's shutdown is called it will terminate run method but
leasecoordinator will wait for 2seconds before releasing the lease. So I
cannot deregister a worker in less than 2 seconds ?

Thanks!



On Mon, Nov 14, 2016 at 7:36 PM, Takeshi Yamamuro 
wrote:

> Is "aws kinesis get-shard-iterator --shard-iterator-type LATEST" not
> enough for your usecase?
>
> On Mon, Nov 14, 2016 at 10:23 PM, Shushant Arora <
> shushantaror...@gmail.com> wrote:
>
>> Thanks!
>> Is there a way to get the latest sequence number of all shards of a
>> kinesis stream?
>>
>>
>>
>> On Mon, Nov 14, 2016 at 5:43 PM, Takeshi Yamamuro 
>> wrote:
>>
>>> Hi,
>>>
>>> The time interval can be controlled by `IdleTimeBetweenReadsInMillis`
>>> in KinesisClientLibConfiguration though,
>>> it is not configurable in the current implementation.
>>>
>>> The detail can be found in;
>>> https://github.com/apache/spark/blob/master/external/kinesis
>>> -asl/src/main/scala/org/apache/spark/streaming/kinesis/
>>> KinesisReceiver.scala#L152
>>>
>>> // maropu
>>>
>>>
>>> On Sun, Nov 13, 2016 at 12:08 AM, Shushant Arora <
>>> shushantaror...@gmail.com> wrote:
>>>
 *Hi *

 *is **spark.streaming.blockInterval* for kinesis input stream is
 hardcoded to 1 sec or is it configurable ? Time interval at which receiver
 fetched data from kinesis .

 Means stream batch interval cannot be less than 
 *spark.streaming.blockInterval
 and this should be configrable , Also is there any minimum value for
 streaming batch interval ?*

 *Thanks*


>>>
>>>
>>> --
>>> ---
>>> Takeshi Yamamuro
>>>
>>
>>
>
>
> --
> ---
> Takeshi Yamamuro
>

Re: spark streaming with kinesis

[Takeshi Yamamuro]

Is "aws kinesis get-shard-iterator --shard-iterator-type LATEST" not enough
for your usecase?

On Mon, Nov 14, 2016 at 10:23 PM, Shushant Arora 
wrote:

> Thanks!
> Is there a way to get the latest sequence number of all shards of a
> kinesis stream?
>
>
>
> On Mon, Nov 14, 2016 at 5:43 PM, Takeshi Yamamuro 
> wrote:
>
>> Hi,
>>
>> The time interval can be controlled by `IdleTimeBetweenReadsInMillis`
>> in KinesisClientLibConfiguration though,
>> it is not configurable in the current implementation.
>>
>> The detail can be found in;
>> https://github.com/apache/spark/blob/master/external/kinesis
>> -asl/src/main/scala/org/apache/spark/streaming/kinesis
>> /KinesisReceiver.scala#L152
>>
>> // maropu
>>
>>
>> On Sun, Nov 13, 2016 at 12:08 AM, Shushant Arora <
>> shushantaror...@gmail.com> wrote:
>>
>>> *Hi *
>>>
>>> *is **spark.streaming.blockInterval* for kinesis input stream is
>>> hardcoded to 1 sec or is it configurable ? Time interval at which receiver
>>> fetched data from kinesis .
>>>
>>> Means stream batch interval cannot be less than 
>>> *spark.streaming.blockInterval
>>> and this should be configrable , Also is there any minimum value for
>>> streaming batch interval ?*
>>>
>>> *Thanks*
>>>
>>>
>>
>>
>> --
>> ---
>> Takeshi Yamamuro
>>
>
>


-- 
---
Takeshi Yamamuro

Re: spark streaming with kinesis

[Shushant Arora]

Thanks!
Is there a way to get the latest sequence number of all shards of a kinesis
stream?



On Mon, Nov 14, 2016 at 5:43 PM, Takeshi Yamamuro 
wrote:

> Hi,
>
> The time interval can be controlled by `IdleTimeBetweenReadsInMillis` in 
> KinesisClientLibConfiguration
> though,
> it is not configurable in the current implementation.
>
> The detail can be found in;
> https://github.com/apache/spark/blob/master/external/
> kinesis-asl/src/main/scala/org/apache/spark/streaming/
> kinesis/KinesisReceiver.scala#L152
>
> // maropu
>
>
> On Sun, Nov 13, 2016 at 12:08 AM, Shushant Arora <
> shushantaror...@gmail.com> wrote:
>
>> *Hi *
>>
>> *is **spark.streaming.blockInterval* for kinesis input stream is
>> hardcoded to 1 sec or is it configurable ? Time interval at which receiver
>> fetched data from kinesis .
>>
>> Means stream batch interval cannot be less than 
>> *spark.streaming.blockInterval
>> and this should be configrable , Also is there any minimum value for
>> streaming batch interval ?*
>>
>> *Thanks*
>>
>>
>
>
> --
> ---
> Takeshi Yamamuro
>

Re: spark streaming with kinesis

[Takeshi Yamamuro]

Hi,

The time interval can be controlled by `IdleTimeBetweenReadsInMillis`
in KinesisClientLibConfiguration though,
it is not configurable in the current implementation.

The detail can be found in;
https://github.com/apache/spark/blob/master/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisReceiver.scala#L152

// maropu


On Sun, Nov 13, 2016 at 12:08 AM, Shushant Arora 
wrote:

> *Hi *
>
> *is **spark.streaming.blockInterval* for kinesis input stream is
> hardcoded to 1 sec or is it configurable ? Time interval at which receiver
> fetched data from kinesis .
>
> Means stream batch interval cannot be less than *spark.streaming.blockInterval
> and this should be configrable , Also is there any minimum value for
> streaming batch interval ?*
>
> *Thanks*
>
>


-- 
---
Takeshi Yamamuro

spark streaming with kinesis

[Shushant Arora]

*Hi *

*is **spark.streaming.blockInterval* for kinesis input stream is hardcoded
to 1 sec or is it configurable ? Time interval at which receiver fetched
data from kinesis .

Means stream batch interval cannot be less than *spark.streaming.blockInterval
and this should be configrable , Also is there any minimum value for
streaming batch interval ?*

*Thanks*

Re: spark streaming with kinesis

[Takeshi Yamamuro]

I'm not familiar with the kafka implementation though, a kinesis receiver
runs in a thread of executors.
You can set any value in the interval, but frequent checkpoints cause
excess loads in dynamodb.
See:
http://spark.apache.org/docs/latest/streaming-kinesis-integration.html#kinesis-checkpointing

// maropu

On Mon, Nov 7, 2016 at 1:36 PM, Shushant Arora 
wrote:

> Hi
>
> By receicer I meant spark streaming receiver architecture- means worker
> nodes are different than receiver nodes. There is no direct consumer/low
> level consumer like of  Kafka in kinesis spark streaming?
>
> Is there any limitation on interval checkpoint - minimum of 1second in
> spark streaming with kinesis. But as such there is no limit on checkpoint
> interval in KCL side ?
>
> Thanks
>
> On Tue, Oct 25, 2016 at 8:36 AM, Takeshi Yamamuro 
> wrote:
>
>> I'm not exactly sure about the receiver you pointed though,
>> if you point the "KinesisReceiver" implementation, yes.
>>
>> Also, we currently cannot disable the interval checkpoints.
>>
>> On Tue, Oct 25, 2016 at 11:53 AM, Shushant Arora <
>> shushantaror...@gmail.com> wrote:
>>
>>> Thanks!
>>>
>>> Is kinesis streams are receiver based only? Is there non receiver based
>>> consumer for Kinesis ?
>>>
>>> And Instead of having fixed checkpoint interval,Can I disable auto
>>> checkpoint and say  when my worker has processed the data after last record
>>> of mapPartition now checkpoint the sequence no using some api.
>>>
>>>
>>>
>>> On Tue, Oct 25, 2016 at 7:07 AM, Takeshi Yamamuro >> > wrote:
>>>
>>>> Hi,
>>>>
>>>> The only thing you can do for Kinesis checkpoints is tune the interval
>>>> of them.
>>>> https://github.com/apache/spark/blob/master/external/kinesis
>>>> -asl/src/main/scala/org/apache/spark/streaming/kinesis/Kines
>>>> isUtils.scala#L68
>>>>
>>>> Whether the dataloss occurs or not depends on the storage level you set;
>>>> if you set StorageLevel.MEMORY_AND_DISK_2, Spark may continue
>>>> processing
>>>> in case of the dataloss because the stream data Spark receives are
>>>> replicated across executors.
>>>> However,  all the executors that have the replicated data crash,
>>>> IIUC the dataloss occurs.
>>>>
>>>> // maropu
>>>>
>>>> On Mon, Oct 24, 2016 at 4:43 PM, Shushant Arora <
>>>> shushantaror...@gmail.com> wrote:
>>>>
>>>>> Does spark streaming consumer for kinesis uses Kinesis Client Library
>>>>>  and mandates to checkpoint the sequence number of shards in dynamo db.
>>>>>
>>>>> Will it lead to dataloss if consumed datarecords are not yet processed
>>>>> and kinesis checkpointed the consumed sequenece numbers in dynamo db and
>>>>> spark worker crashes - then spark launched the worker on another node but
>>>>> start consuming from dynamo db's checkpointed sequence number which is
>>>>> ahead of processed sequenece number .
>>>>>
>>>>> is there a way to checkpoint the sequenece numbers ourselves in
>>>>> Kinesis as it is in Kafka low level consumer ?
>>>>>
>>>>> Thanks
>>>>>
>>>>>
>>>>
>>>>
>>>> --
>>>> ---
>>>> Takeshi Yamamuro
>>>>
>>>
>>>
>>
>>
>> --
>> ---
>> Takeshi Yamamuro
>>
>
>


-- 
---
Takeshi Yamamuro

Re: spark streaming with kinesis

[Shushant Arora]

Hi

By receicer I meant spark streaming receiver architecture- means worker
nodes are different than receiver nodes. There is no direct consumer/low
level consumer like of  Kafka in kinesis spark streaming?

Is there any limitation on interval checkpoint - minimum of 1second in
spark streaming with kinesis. But as such there is no limit on checkpoint
interval in KCL side ?

Thanks

On Tue, Oct 25, 2016 at 8:36 AM, Takeshi Yamamuro 
wrote:

> I'm not exactly sure about the receiver you pointed though,
> if you point the "KinesisReceiver" implementation, yes.
>
> Also, we currently cannot disable the interval checkpoints.
>
> On Tue, Oct 25, 2016 at 11:53 AM, Shushant Arora <
> shushantaror...@gmail.com> wrote:
>
>> Thanks!
>>
>> Is kinesis streams are receiver based only? Is there non receiver based
>> consumer for Kinesis ?
>>
>> And Instead of having fixed checkpoint interval,Can I disable auto
>> checkpoint and say  when my worker has processed the data after last record
>> of mapPartition now checkpoint the sequence no using some api.
>>
>>
>>
>> On Tue, Oct 25, 2016 at 7:07 AM, Takeshi Yamamuro 
>> wrote:
>>
>>> Hi,
>>>
>>> The only thing you can do for Kinesis checkpoints is tune the interval
>>> of them.
>>> https://github.com/apache/spark/blob/master/external/kinesis
>>> -asl/src/main/scala/org/apache/spark/streaming/kinesis/Kines
>>> isUtils.scala#L68
>>>
>>> Whether the dataloss occurs or not depends on the storage level you set;
>>> if you set StorageLevel.MEMORY_AND_DISK_2, Spark may continue processing
>>> in case of the dataloss because the stream data Spark receives are
>>> replicated across executors.
>>> However,  all the executors that have the replicated data crash,
>>> IIUC the dataloss occurs.
>>>
>>> // maropu
>>>
>>> On Mon, Oct 24, 2016 at 4:43 PM, Shushant Arora <
>>> shushantaror...@gmail.com> wrote:
>>>
>>>> Does spark streaming consumer for kinesis uses Kinesis Client Library
>>>>  and mandates to checkpoint the sequence number of shards in dynamo db.
>>>>
>>>> Will it lead to dataloss if consumed datarecords are not yet processed
>>>> and kinesis checkpointed the consumed sequenece numbers in dynamo db and
>>>> spark worker crashes - then spark launched the worker on another node but
>>>> start consuming from dynamo db's checkpointed sequence number which is
>>>> ahead of processed sequenece number .
>>>>
>>>> is there a way to checkpoint the sequenece numbers ourselves in Kinesis
>>>> as it is in Kafka low level consumer ?
>>>>
>>>> Thanks
>>>>
>>>>
>>>
>>>
>>> --
>>> ---
>>> Takeshi Yamamuro
>>>
>>
>>
>
>
> --
> ---
> Takeshi Yamamuro
>

Re: spark streaming with kinesis

[Takeshi Yamamuro]

I'm not exactly sure about the receiver you pointed though,
if you point the "KinesisReceiver" implementation, yes.

Also, we currently cannot disable the interval checkpoints.

On Tue, Oct 25, 2016 at 11:53 AM, Shushant Arora 
wrote:

> Thanks!
>
> Is kinesis streams are receiver based only? Is there non receiver based
> consumer for Kinesis ?
>
> And Instead of having fixed checkpoint interval,Can I disable auto
> checkpoint and say  when my worker has processed the data after last record
> of mapPartition now checkpoint the sequence no using some api.
>
>
>
> On Tue, Oct 25, 2016 at 7:07 AM, Takeshi Yamamuro 
> wrote:
>
>> Hi,
>>
>> The only thing you can do for Kinesis checkpoints is tune the interval of
>> them.
>> https://github.com/apache/spark/blob/master/external/kinesis
>> -asl/src/main/scala/org/apache/spark/streaming/kinesis/
>> KinesisUtils.scala#L68
>>
>> Whether the dataloss occurs or not depends on the storage level you set;
>> if you set StorageLevel.MEMORY_AND_DISK_2, Spark may continue processing
>> in case of the dataloss because the stream data Spark receives are
>> replicated across executors.
>> However,  all the executors that have the replicated data crash,
>> IIUC the dataloss occurs.
>>
>> // maropu
>>
>> On Mon, Oct 24, 2016 at 4:43 PM, Shushant Arora <
>> shushantaror...@gmail.com> wrote:
>>
>>> Does spark streaming consumer for kinesis uses Kinesis Client Library
>>>  and mandates to checkpoint the sequence number of shards in dynamo db.
>>>
>>> Will it lead to dataloss if consumed datarecords are not yet processed
>>> and kinesis checkpointed the consumed sequenece numbers in dynamo db and
>>> spark worker crashes - then spark launched the worker on another node but
>>> start consuming from dynamo db's checkpointed sequence number which is
>>> ahead of processed sequenece number .
>>>
>>> is there a way to checkpoint the sequenece numbers ourselves in Kinesis
>>> as it is in Kafka low level consumer ?
>>>
>>> Thanks
>>>
>>>
>>
>>
>> --
>> ---
>> Takeshi Yamamuro
>>
>
>


-- 
---
Takeshi Yamamuro

Re: spark streaming with kinesis

[Shushant Arora]

Thanks!

Is kinesis streams are receiver based only? Is there non receiver based
consumer for Kinesis ?

And Instead of having fixed checkpoint interval,Can I disable auto
checkpoint and say  when my worker has processed the data after last record
of mapPartition now checkpoint the sequence no using some api.



On Tue, Oct 25, 2016 at 7:07 AM, Takeshi Yamamuro 
wrote:

> Hi,
>
> The only thing you can do for Kinesis checkpoints is tune the interval of
> them.
> https://github.com/apache/spark/blob/master/external/kinesis
> -asl/src/main/scala/org/apache/spark/streaming/kinesis
> /KinesisUtils.scala#L68
>
> Whether the dataloss occurs or not depends on the storage level you set;
> if you set StorageLevel.MEMORY_AND_DISK_2, Spark may continue processing
> in case of the dataloss because the stream data Spark receives are
> replicated across executors.
> However,  all the executors that have the replicated data crash,
> IIUC the dataloss occurs.
>
> // maropu
>
> On Mon, Oct 24, 2016 at 4:43 PM, Shushant Arora  > wrote:
>
>> Does spark streaming consumer for kinesis uses Kinesis Client Library
>>  and mandates to checkpoint the sequence number of shards in dynamo db.
>>
>> Will it lead to dataloss if consumed datarecords are not yet processed
>> and kinesis checkpointed the consumed sequenece numbers in dynamo db and
>> spark worker crashes - then spark launched the worker on another node but
>> start consuming from dynamo db's checkpointed sequence number which is
>> ahead of processed sequenece number .
>>
>> is there a way to checkpoint the sequenece numbers ourselves in Kinesis
>> as it is in Kafka low level consumer ?
>>
>> Thanks
>>
>>
>
>
> --
> ---
> Takeshi Yamamuro
>

Re: spark streaming with kinesis

[Takeshi Yamamuro]

Hi,

The only thing you can do for Kinesis checkpoints is tune the interval of
them.
https://github.com/apache/spark/blob/master/external/
kinesis-asl/src/main/scala/org/apache/spark/streaming/
kinesis/KinesisUtils.scala#L68

Whether the dataloss occurs or not depends on the storage level you set;
if you set StorageLevel.MEMORY_AND_DISK_2, Spark may continue processing
in case of the dataloss because the stream data Spark receives are
replicated across executors.
However,  all the executors that have the replicated data crash,
IIUC the dataloss occurs.

// maropu

On Mon, Oct 24, 2016 at 4:43 PM, Shushant Arora 
wrote:

> Does spark streaming consumer for kinesis uses Kinesis Client Library
>  and mandates to checkpoint the sequence number of shards in dynamo db.
>
> Will it lead to dataloss if consumed datarecords are not yet processed and
> kinesis checkpointed the consumed sequenece numbers in dynamo db and spark
> worker crashes - then spark launched the worker on another node but start
> consuming from dynamo db's checkpointed sequence number which is ahead of
> processed sequenece number .
>
> is there a way to checkpoint the sequenece numbers ourselves in Kinesis as
> it is in Kafka low level consumer ?
>
> Thanks
>
>


-- 
---
Takeshi Yamamuro

spark streaming with kinesis

[Shushant Arora]

Does spark streaming consumer for kinesis uses Kinesis Client Library  and
mandates to checkpoint the sequence number of shards in dynamo db.

Will it lead to dataloss if consumed datarecords are not yet processed and
kinesis checkpointed the consumed sequenece numbers in dynamo db and spark
worker crashes - then spark launched the worker on another node but start
consuming from dynamo db's checkpointed sequence number which is ahead of
processed sequenece number .

is there a way to checkpoint the sequenece numbers ourselves in Kinesis as
it is in Kafka low level consumer ?

Thanks

Re: Spark streaming with Kinesis broken?

[Brian London]

Yes, it's against master: https://github.com/apache/spark/pull/10256

I'll push the KCL version bump after my local tests finish.

On Fri, Dec 11, 2015 at 10:42 AM Nick Pentreath 
wrote:

> Is that PR against master branch?
>
> S3 read comes from Hadoop / jet3t afaik
>
> —
> Sent from Mailbox 
>
>
> On Fri, Dec 11, 2015 at 5:38 PM, Brian London 
> wrote:
>
>> That's good news  I've got a PR in to up the SDK version to 1.10.40 and
>> the KCL to 1.6.1 which I'm running tests on locally now.
>>
>> Is the AWS SDK not used for reading/writing from S3 or do we get that for
>> free from the Hadoop dependencies?
>>
>> On Fri, Dec 11, 2015 at 5:07 AM Nick Pentreath 
>> wrote:
>>
>>> cc'ing dev list
>>>
>>> Ok, looks like when the KCL version was updated in
>>> https://github.com/apache/spark/pull/8957, the AWS SDK version was not,
>>> probably leading to dependency conflict, though as Burak mentions its hard
>>> to debug as no exceptions seem to get thrown... I've tested 1.5.2 locally
>>> and on my 1.5.2 EC2 cluster, and no data is received, and nothing shows up
>>> in driver or worker logs, so any exception is getting swallowed somewhere.
>>>
>>> Run starting. Expected test count is: 4
>>> KinesisStreamSuite:
>>> Using endpoint URL https://kinesis.eu-west-1.amazonaws.com for creating
>>> Kinesis streams for tests.
>>> - KinesisUtils API
>>> - RDD generation
>>> - basic operation *** FAILED ***
>>>   The code passed to eventually never returned normally. Attempted 13
>>> times over 2.04 minutes. Last failure message: Set() did not equal
>>> Set(5, 10, 1, 6, 9, 2, 7, 3, 8, 4)
>>>   Data received does not match data sent. (KinesisStreamSuite.scala:188)
>>> - failure recovery *** FAILED ***
>>>   The code passed to eventually never returned normally. Attempted 63
>>> times over 2.02863831 minutes. Last failure message:
>>> isCheckpointPresent was true, but 0 was not greater than 10.
>>> (KinesisStreamSuite.scala:228)
>>> Run completed in 5 minutes, 0 seconds.
>>> Total number of tests run: 4
>>> Suites: completed 1, aborted 0
>>> Tests: succeeded 2, failed 2, canceled 0, ignored 0, pending 0
>>> *** 2 TESTS FAILED ***
>>> [INFO]
>>> 
>>> [INFO] BUILD FAILURE
>>> [INFO]
>>> 
>>>
>>>
>>> KCL 1.3.0 depends on *1.9.37* SDK (
>>> https://github.com/awslabs/amazon-kinesis-client/blob/1.3.0/pom.xml#L26)
>>> while the Spark Kinesis dependency was kept at *1.9.16.*
>>>
>>> I've run the integration tests on branch-1.5 (1.5.3-SNAPSHOT) with AWS
>>> SDK 1.9.37 and everything works.
>>>
>>> Run starting. Expected test count is: 28
>>> KinesisBackedBlockRDDSuite:
>>> Using endpoint URL https://kinesis.eu-west-1.amazonaws.com for creating
>>> Kinesis streams for tests.
>>> - Basic reading from Kinesis
>>> - Read data available in both block manager and Kinesis
>>> - Read data available only in block manager, not in Kinesis
>>> - Read data available only in Kinesis, not in block manager
>>> - Read data available partially in block manager, rest in Kinesis
>>> - Test isBlockValid skips block fetching from block manager
>>> - Test whether RDD is valid after removing blocks from block anager
>>> KinesisStreamSuite:
>>> - KinesisUtils API
>>> - RDD generation
>>> - basic operation
>>> - failure recovery
>>> KinesisReceiverSuite:
>>> - check serializability of SerializableAWSCredentials
>>> - process records including store and checkpoint
>>> - shouldn't store and checkpoint when receiver is stopped
>>> - shouldn't checkpoint when exception occurs during store
>>> - should set checkpoint time to currentTime + checkpoint interval upon
>>> instantiation
>>> - should checkpoint if we have exceeded the checkpoint interval
>>> - shouldn't checkpoint if we have not exceeded the checkpoint interval
>>> - should add to time when advancing checkpoint
>>> - shutdown should checkpoint if the reason is TERMINATE
>>> - shutdown should not checkpoint if the reason is something other than
>>> TERMINATE
>>> - retry success on first attempt
>>> - retry success on second attempt after a Kinesis throttling exception
>>> - retry success on second attempt after a Kinesis dependency exception
>>> - retry failed after a shutdown exception
>>> - retry failed after an invalid state exception
>>> - retry failed after unexpected exception
>>> - retry failed after exhausing all retries
>>> Run completed in 3 minutes, 28 seconds.
>>> Total number of tests run: 28
>>> Suites: completed 4, aborted 0
>>> Tests: succeeded 28, failed 0, canceled 0, ignored 0, pending 0
>>> All tests passed.
>>>
>>> So this is a regression in Spark Streaming Kinesis 1.5.2 - @Brian can
>>> you file a JIRA for this?
>>>
>>> @dev-list, since KCL brings in AWS SDK dependencies itself, is it
>>> necessary to declare an explicit dependency on aws-java-sdk in the Kinesis
>>> POM? Also, from KCL 1.5.0+, only the

Re: Spark streaming with Kinesis broken?

[Nick Pentreath]

Is that PR against master branch?




S3 read comes from Hadoop / jet3t afaik



—
Sent from Mailbox

On Fri, Dec 11, 2015 at 5:38 PM, Brian London 
wrote:

> That's good news  I've got a PR in to up the SDK version to 1.10.40 and the
> KCL to 1.6.1 which I'm running tests on locally now.
> Is the AWS SDK not used for reading/writing from S3 or do we get that for
> free from the Hadoop dependencies?
> On Fri, Dec 11, 2015 at 5:07 AM Nick Pentreath 
> wrote:
>> cc'ing dev list
>>
>> Ok, looks like when the KCL version was updated in
>> https://github.com/apache/spark/pull/8957, the AWS SDK version was not,
>> probably leading to dependency conflict, though as Burak mentions its hard
>> to debug as no exceptions seem to get thrown... I've tested 1.5.2 locally
>> and on my 1.5.2 EC2 cluster, and no data is received, and nothing shows up
>> in driver or worker logs, so any exception is getting swallowed somewhere.
>>
>> Run starting. Expected test count is: 4
>> KinesisStreamSuite:
>> Using endpoint URL https://kinesis.eu-west-1.amazonaws.com for creating
>> Kinesis streams for tests.
>> - KinesisUtils API
>> - RDD generation
>> - basic operation *** FAILED ***
>>   The code passed to eventually never returned normally. Attempted 13
>> times over 2.04 minutes. Last failure message: Set() did not equal
>> Set(5, 10, 1, 6, 9, 2, 7, 3, 8, 4)
>>   Data received does not match data sent. (KinesisStreamSuite.scala:188)
>> - failure recovery *** FAILED ***
>>   The code passed to eventually never returned normally. Attempted 63
>> times over 2.02863831 minutes. Last failure message:
>> isCheckpointPresent was true, but 0 was not greater than 10.
>> (KinesisStreamSuite.scala:228)
>> Run completed in 5 minutes, 0 seconds.
>> Total number of tests run: 4
>> Suites: completed 1, aborted 0
>> Tests: succeeded 2, failed 2, canceled 0, ignored 0, pending 0
>> *** 2 TESTS FAILED ***
>> [INFO]
>> 
>> [INFO] BUILD FAILURE
>> [INFO]
>> 
>>
>>
>> KCL 1.3.0 depends on *1.9.37* SDK (
>> https://github.com/awslabs/amazon-kinesis-client/blob/1.3.0/pom.xml#L26)
>> while the Spark Kinesis dependency was kept at *1.9.16.*
>>
>> I've run the integration tests on branch-1.5 (1.5.3-SNAPSHOT) with AWS SDK
>> 1.9.37 and everything works.
>>
>> Run starting. Expected test count is: 28
>> KinesisBackedBlockRDDSuite:
>> Using endpoint URL https://kinesis.eu-west-1.amazonaws.com for creating
>> Kinesis streams for tests.
>> - Basic reading from Kinesis
>> - Read data available in both block manager and Kinesis
>> - Read data available only in block manager, not in Kinesis
>> - Read data available only in Kinesis, not in block manager
>> - Read data available partially in block manager, rest in Kinesis
>> - Test isBlockValid skips block fetching from block manager
>> - Test whether RDD is valid after removing blocks from block anager
>> KinesisStreamSuite:
>> - KinesisUtils API
>> - RDD generation
>> - basic operation
>> - failure recovery
>> KinesisReceiverSuite:
>> - check serializability of SerializableAWSCredentials
>> - process records including store and checkpoint
>> - shouldn't store and checkpoint when receiver is stopped
>> - shouldn't checkpoint when exception occurs during store
>> - should set checkpoint time to currentTime + checkpoint interval upon
>> instantiation
>> - should checkpoint if we have exceeded the checkpoint interval
>> - shouldn't checkpoint if we have not exceeded the checkpoint interval
>> - should add to time when advancing checkpoint
>> - shutdown should checkpoint if the reason is TERMINATE
>> - shutdown should not checkpoint if the reason is something other than
>> TERMINATE
>> - retry success on first attempt
>> - retry success on second attempt after a Kinesis throttling exception
>> - retry success on second attempt after a Kinesis dependency exception
>> - retry failed after a shutdown exception
>> - retry failed after an invalid state exception
>> - retry failed after unexpected exception
>> - retry failed after exhausing all retries
>> Run completed in 3 minutes, 28 seconds.
>> Total number of tests run: 28
>> Suites: completed 4, aborted 0
>> Tests: succeeded 28, failed 0, canceled 0, ignored 0, pending 0
>> All tests passed.
>>
>> So this is a regression in Spark Streaming Kinesis 1.5.2 - @Brian can you
>> file a JIRA for this?
>>
>> @dev-list, since KCL brings in AWS SDK dependencies itself, is it
>> necessary to declare an explicit dependency on aws-java-sdk in the Kinesis
>> POM? Also, from KCL 1.5.0+, only the relevant components used from the AWS
>> SDKs are brought in, making things a bit leaner (this can be upgraded in
>> Spark 1.7/2.0 perhaps). All local tests (and integration tests) pass with
>> removing the explicit dependency and only depending on KCL. Is aws-java-sdk
>> used anywhere else (AFAIK it is not, but in case I missed something 

Re: Spark streaming with Kinesis broken?

[Brian London]

That's good news  I've got a PR in to up the SDK version to 1.10.40 and the
KCL to 1.6.1 which I'm running tests on locally now.

Is the AWS SDK not used for reading/writing from S3 or do we get that for
free from the Hadoop dependencies?

On Fri, Dec 11, 2015 at 5:07 AM Nick Pentreath 
wrote:

> cc'ing dev list
>
> Ok, looks like when the KCL version was updated in
> https://github.com/apache/spark/pull/8957, the AWS SDK version was not,
> probably leading to dependency conflict, though as Burak mentions its hard
> to debug as no exceptions seem to get thrown... I've tested 1.5.2 locally
> and on my 1.5.2 EC2 cluster, and no data is received, and nothing shows up
> in driver or worker logs, so any exception is getting swallowed somewhere.
>
> Run starting. Expected test count is: 4
> KinesisStreamSuite:
> Using endpoint URL https://kinesis.eu-west-1.amazonaws.com for creating
> Kinesis streams for tests.
> - KinesisUtils API
> - RDD generation
> - basic operation *** FAILED ***
>   The code passed to eventually never returned normally. Attempted 13
> times over 2.04 minutes. Last failure message: Set() did not equal
> Set(5, 10, 1, 6, 9, 2, 7, 3, 8, 4)
>   Data received does not match data sent. (KinesisStreamSuite.scala:188)
> - failure recovery *** FAILED ***
>   The code passed to eventually never returned normally. Attempted 63
> times over 2.02863831 minutes. Last failure message:
> isCheckpointPresent was true, but 0 was not greater than 10.
> (KinesisStreamSuite.scala:228)
> Run completed in 5 minutes, 0 seconds.
> Total number of tests run: 4
> Suites: completed 1, aborted 0
> Tests: succeeded 2, failed 2, canceled 0, ignored 0, pending 0
> *** 2 TESTS FAILED ***
> [INFO]
> 
> [INFO] BUILD FAILURE
> [INFO]
> 
>
>
> KCL 1.3.0 depends on *1.9.37* SDK (
> https://github.com/awslabs/amazon-kinesis-client/blob/1.3.0/pom.xml#L26)
> while the Spark Kinesis dependency was kept at *1.9.16.*
>
> I've run the integration tests on branch-1.5 (1.5.3-SNAPSHOT) with AWS SDK
> 1.9.37 and everything works.
>
> Run starting. Expected test count is: 28
> KinesisBackedBlockRDDSuite:
> Using endpoint URL https://kinesis.eu-west-1.amazonaws.com for creating
> Kinesis streams for tests.
> - Basic reading from Kinesis
> - Read data available in both block manager and Kinesis
> - Read data available only in block manager, not in Kinesis
> - Read data available only in Kinesis, not in block manager
> - Read data available partially in block manager, rest in Kinesis
> - Test isBlockValid skips block fetching from block manager
> - Test whether RDD is valid after removing blocks from block anager
> KinesisStreamSuite:
> - KinesisUtils API
> - RDD generation
> - basic operation
> - failure recovery
> KinesisReceiverSuite:
> - check serializability of SerializableAWSCredentials
> - process records including store and checkpoint
> - shouldn't store and checkpoint when receiver is stopped
> - shouldn't checkpoint when exception occurs during store
> - should set checkpoint time to currentTime + checkpoint interval upon
> instantiation
> - should checkpoint if we have exceeded the checkpoint interval
> - shouldn't checkpoint if we have not exceeded the checkpoint interval
> - should add to time when advancing checkpoint
> - shutdown should checkpoint if the reason is TERMINATE
> - shutdown should not checkpoint if the reason is something other than
> TERMINATE
> - retry success on first attempt
> - retry success on second attempt after a Kinesis throttling exception
> - retry success on second attempt after a Kinesis dependency exception
> - retry failed after a shutdown exception
> - retry failed after an invalid state exception
> - retry failed after unexpected exception
> - retry failed after exhausing all retries
> Run completed in 3 minutes, 28 seconds.
> Total number of tests run: 28
> Suites: completed 4, aborted 0
> Tests: succeeded 28, failed 0, canceled 0, ignored 0, pending 0
> All tests passed.
>
> So this is a regression in Spark Streaming Kinesis 1.5.2 - @Brian can you
> file a JIRA for this?
>
> @dev-list, since KCL brings in AWS SDK dependencies itself, is it
> necessary to declare an explicit dependency on aws-java-sdk in the Kinesis
> POM? Also, from KCL 1.5.0+, only the relevant components used from the AWS
> SDKs are brought in, making things a bit leaner (this can be upgraded in
> Spark 1.7/2.0 perhaps). All local tests (and integration tests) pass with
> removing the explicit dependency and only depending on KCL. Is aws-java-sdk
> used anywhere else (AFAIK it is not, but in case I missed something let me
> know any good reason to keep the explicit dependency)?
>
> N
>
>
>
> On Fri, Dec 11, 2015 at 6:55 AM, Nick Pentreath 
> wrote:
>
>> Yeah also the integration tests need to be specifically run - I would
>> have thought the contributor would have run thos

Re: Spark streaming with Kinesis broken?

[Nick Pentreath]

cc'ing dev list

Ok, looks like when the KCL version was updated in
https://github.com/apache/spark/pull/8957, the AWS SDK version was not,
probably leading to dependency conflict, though as Burak mentions its hard
to debug as no exceptions seem to get thrown... I've tested 1.5.2 locally
and on my 1.5.2 EC2 cluster, and no data is received, and nothing shows up
in driver or worker logs, so any exception is getting swallowed somewhere.

Run starting. Expected test count is: 4
KinesisStreamSuite:
Using endpoint URL https://kinesis.eu-west-1.amazonaws.com for creating
Kinesis streams for tests.
- KinesisUtils API
- RDD generation
- basic operation *** FAILED ***
  The code passed to eventually never returned normally. Attempted 13 times
over 2.04 minutes. Last failure message: Set() did not equal Set(5, 10,
1, 6, 9, 2, 7, 3, 8, 4)
  Data received does not match data sent. (KinesisStreamSuite.scala:188)
- failure recovery *** FAILED ***
  The code passed to eventually never returned normally. Attempted 63 times
over 2.02863831 minutes. Last failure message: isCheckpointPresent
was true, but 0 was not greater than 10. (KinesisStreamSuite.scala:228)
Run completed in 5 minutes, 0 seconds.
Total number of tests run: 4
Suites: completed 1, aborted 0
Tests: succeeded 2, failed 2, canceled 0, ignored 0, pending 0
*** 2 TESTS FAILED ***
[INFO]

[INFO] BUILD FAILURE
[INFO]



KCL 1.3.0 depends on *1.9.37* SDK (
https://github.com/awslabs/amazon-kinesis-client/blob/1.3.0/pom.xml#L26)
while the Spark Kinesis dependency was kept at *1.9.16.*

I've run the integration tests on branch-1.5 (1.5.3-SNAPSHOT) with AWS SDK
1.9.37 and everything works.

Run starting. Expected test count is: 28
KinesisBackedBlockRDDSuite:
Using endpoint URL https://kinesis.eu-west-1.amazonaws.com for creating
Kinesis streams for tests.
- Basic reading from Kinesis
- Read data available in both block manager and Kinesis
- Read data available only in block manager, not in Kinesis
- Read data available only in Kinesis, not in block manager
- Read data available partially in block manager, rest in Kinesis
- Test isBlockValid skips block fetching from block manager
- Test whether RDD is valid after removing blocks from block anager
KinesisStreamSuite:
- KinesisUtils API
- RDD generation
- basic operation
- failure recovery
KinesisReceiverSuite:
- check serializability of SerializableAWSCredentials
- process records including store and checkpoint
- shouldn't store and checkpoint when receiver is stopped
- shouldn't checkpoint when exception occurs during store
- should set checkpoint time to currentTime + checkpoint interval upon
instantiation
- should checkpoint if we have exceeded the checkpoint interval
- shouldn't checkpoint if we have not exceeded the checkpoint interval
- should add to time when advancing checkpoint
- shutdown should checkpoint if the reason is TERMINATE
- shutdown should not checkpoint if the reason is something other than
TERMINATE
- retry success on first attempt
- retry success on second attempt after a Kinesis throttling exception
- retry success on second attempt after a Kinesis dependency exception
- retry failed after a shutdown exception
- retry failed after an invalid state exception
- retry failed after unexpected exception
- retry failed after exhausing all retries
Run completed in 3 minutes, 28 seconds.
Total number of tests run: 28
Suites: completed 4, aborted 0
Tests: succeeded 28, failed 0, canceled 0, ignored 0, pending 0
All tests passed.

So this is a regression in Spark Streaming Kinesis 1.5.2 - @Brian can you
file a JIRA for this?

@dev-list, since KCL brings in AWS SDK dependencies itself, is it necessary
to declare an explicit dependency on aws-java-sdk in the Kinesis POM? Also,
from KCL 1.5.0+, only the relevant components used from the AWS SDKs are
brought in, making things a bit leaner (this can be upgraded in Spark
1.7/2.0 perhaps). All local tests (and integration tests) pass with
removing the explicit dependency and only depending on KCL. Is aws-java-sdk
used anywhere else (AFAIK it is not, but in case I missed something let me
know any good reason to keep the explicit dependency)?

N



On Fri, Dec 11, 2015 at 6:55 AM, Nick Pentreath 
wrote:

> Yeah also the integration tests need to be specifically run - I would have
> thought the contributor would have run those tests and also tested the
> change themselves using live Kinesis :(
>
> —
> Sent from Mailbox 
>
>
> On Fri, Dec 11, 2015 at 6:18 AM, Burak Yavuz  wrote:
>
>> I don't think the Kinesis tests specifically ran when that was merged
>> into 1.5.2 :(
>> https://github.com/apache/spark/pull/8957
>>
>> https://github.com/apache/spark/commit/883bd8fccf83aae7a2a847c9a6ca129fac86e6a3
>>
>> AFAIK pom changes don't trigger the Kinesis tests.
>>
>> Burak
>>
>> On Thu, 

Re: Spark streaming with Kinesis broken?

[Nick Pentreath]

Yeah also the integration tests need to be specifically run - I would have 
thought the contributor would have run those tests and also tested the change 
themselves using live Kinesis :(



—
Sent from Mailbox

On Fri, Dec 11, 2015 at 6:18 AM, Burak Yavuz  wrote:

> I don't think the Kinesis tests specifically ran when that was merged into
> 1.5.2 :(
> https://github.com/apache/spark/pull/8957
> https://github.com/apache/spark/commit/883bd8fccf83aae7a2a847c9a6ca129fac86e6a3
> AFAIK pom changes don't trigger the Kinesis tests.
> Burak
> On Thu, Dec 10, 2015 at 8:09 PM, Nick Pentreath 
> wrote:
>> Yup also works for me on master branch as I've been testing DynamoDB
>> Streams integration. In fact works with latest KCL 1.6.1 also which I was
>> using.
>>
>> So theKCL version does seem like it could be the issue - somewhere along
>> the line an exception must be getting swallowed. Though the tests should
>> have picked this up? Will dig deeper.
>>
>> —
>> Sent from Mailbox 
>>
>>
>> On Thu, Dec 10, 2015 at 11:07 PM, Brian London 
>> wrote:
>>
>>> Yes, it worked in the 1.6 branch as of commit
>>> db5165246f2888537dd0f3d4c5a515875c7358ed.  That makes it much less
>>> serious of an issue, although it would be nice to know what the root cause
>>> is to avoid a regression.
>>>
>>> On Thu, Dec 10, 2015 at 4:03 PM Burak Yavuz  wrote:
>>>
 I've noticed this happening when there was some dependency conflicts,
 and it is super hard to debug.
 It seems that the KinesisClientLibrary version in Spark 1.5.2 is 1.3.0,
 but it is 1.2.1 in Spark 1.5.1.
 I feel like that seems to be the problem...

 Brian, did you verify that it works with the 1.6.0 branch?

 Thanks,
 Burak

 On Thu, Dec 10, 2015 at 11:45 AM, Brian London 
 wrote:

> Nick's symptoms sound identical to mine.  I should mention that I just
> pulled the latest version from github and it seems to be working there.  
> To
> reproduce:
>
>
>1. Download spark 1.5.2 from http://spark.apache.org/downloads.html
>2. build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.6.0 -DskipTests
>clean package
>3. build/mvn -Pkinesis-asl -DskipTests clean package
>4. Then run simultaneously:
>1. bin/run-example streaming.KinesisWordCountASL [Kinesis app name]
>   [Kinesis stream name] [endpoint URL]
>   2.   bin/run-example streaming.KinesisWordProducerASL [Kinesis
>   stream name] [endpoint URL] 100 10
>
>
> On Thu, Dec 10, 2015 at 2:05 PM Jean-Baptiste Onofré 
> wrote:
>
>> Hi Nick,
>>
>> Just to be sure: don't you see some ClassCastException in the log ?
>>
>> Thanks,
>> Regards
>> JB
>>
>> On 12/10/2015 07:56 PM, Nick Pentreath wrote:
>> > Could you provide an example / test case and more detail on what
>> issue
>> > you're facing?
>> >
>> > I've just tested a simple program reading from a dev Kinesis stream
>> and
>> > using stream.print() to show the records, and it works under 1.5.1
>> but
>> > doesn't appear to be working under 1.5.2.
>> >
>> > UI for 1.5.2:
>> >
>> > Inline image 1
>> >
>> > UI for 1.5.1:
>> >
>> > Inline image 2
>> >
>> > On Thu, Dec 10, 2015 at 5:50 PM, Brian London <
>> brianmlon...@gmail.com
>> > > wrote:
>> >
>> > Has anyone managed to run the Kinesis demo in Spark 1.5.2?  The
>> > Kinesis ASL that ships with 1.5.2 appears to not work for me
>> > although 1.5.1 is fine. I spent some time with Amazon earlier in
>> the
>> > week and the only thing we could do to make it work is to change
>> the
>> > version to 1.5.1.  Can someone please attempt to reproduce
>> before I
>> > open a JIRA issue for it?
>> >
>> >
>>
>> --
>> Jean-Baptiste Onofré
>> jbono...@apache.org
>> http://blog.nanthrax.net
>> Talend - http://www.talend.com
>>
>> -
>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
>> For additional commands, e-mail: user-h...@spark.apache.org
>>
>>

>>

Re: Spark streaming with Kinesis broken?

[Burak Yavuz]

I don't think the Kinesis tests specifically ran when that was merged into
1.5.2 :(
https://github.com/apache/spark/pull/8957
https://github.com/apache/spark/commit/883bd8fccf83aae7a2a847c9a6ca129fac86e6a3

AFAIK pom changes don't trigger the Kinesis tests.

Burak

On Thu, Dec 10, 2015 at 8:09 PM, Nick Pentreath 
wrote:

> Yup also works for me on master branch as I've been testing DynamoDB
> Streams integration. In fact works with latest KCL 1.6.1 also which I was
> using.
>
> So theKCL version does seem like it could be the issue - somewhere along
> the line an exception must be getting swallowed. Though the tests should
> have picked this up? Will dig deeper.
>
> —
> Sent from Mailbox 
>
>
> On Thu, Dec 10, 2015 at 11:07 PM, Brian London 
> wrote:
>
>> Yes, it worked in the 1.6 branch as of commit
>> db5165246f2888537dd0f3d4c5a515875c7358ed.  That makes it much less
>> serious of an issue, although it would be nice to know what the root cause
>> is to avoid a regression.
>>
>> On Thu, Dec 10, 2015 at 4:03 PM Burak Yavuz  wrote:
>>
>>> I've noticed this happening when there was some dependency conflicts,
>>> and it is super hard to debug.
>>> It seems that the KinesisClientLibrary version in Spark 1.5.2 is 1.3.0,
>>> but it is 1.2.1 in Spark 1.5.1.
>>> I feel like that seems to be the problem...
>>>
>>> Brian, did you verify that it works with the 1.6.0 branch?
>>>
>>> Thanks,
>>> Burak
>>>
>>> On Thu, Dec 10, 2015 at 11:45 AM, Brian London 
>>> wrote:
>>>
 Nick's symptoms sound identical to mine.  I should mention that I just
 pulled the latest version from github and it seems to be working there.  To
 reproduce:


1. Download spark 1.5.2 from http://spark.apache.org/downloads.html
2. build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.6.0 -DskipTests
clean package
3. build/mvn -Pkinesis-asl -DskipTests clean package
4. Then run simultaneously:
1. bin/run-example streaming.KinesisWordCountASL [Kinesis app name]
   [Kinesis stream name] [endpoint URL]
   2.   bin/run-example streaming.KinesisWordProducerASL [Kinesis
   stream name] [endpoint URL] 100 10


 On Thu, Dec 10, 2015 at 2:05 PM Jean-Baptiste Onofré 
 wrote:

> Hi Nick,
>
> Just to be sure: don't you see some ClassCastException in the log ?
>
> Thanks,
> Regards
> JB
>
> On 12/10/2015 07:56 PM, Nick Pentreath wrote:
> > Could you provide an example / test case and more detail on what
> issue
> > you're facing?
> >
> > I've just tested a simple program reading from a dev Kinesis stream
> and
> > using stream.print() to show the records, and it works under 1.5.1
> but
> > doesn't appear to be working under 1.5.2.
> >
> > UI for 1.5.2:
> >
> > Inline image 1
> >
> > UI for 1.5.1:
> >
> > Inline image 2
> >
> > On Thu, Dec 10, 2015 at 5:50 PM, Brian London <
> brianmlon...@gmail.com
> > > wrote:
> >
> > Has anyone managed to run the Kinesis demo in Spark 1.5.2?  The
> > Kinesis ASL that ships with 1.5.2 appears to not work for me
> > although 1.5.1 is fine. I spent some time with Amazon earlier in
> the
> > week and the only thing we could do to make it work is to change
> the
> > version to 1.5.1.  Can someone please attempt to reproduce
> before I
> > open a JIRA issue for it?
> >
> >
>
> --
> Jean-Baptiste Onofré
> jbono...@apache.org
> http://blog.nanthrax.net
> Talend - http://www.talend.com
>
> -
> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
> For additional commands, e-mail: user-h...@spark.apache.org
>
>
>>>
>

Re: Spark streaming with Kinesis broken?

[Nick Pentreath]

Yup also works for me on master branch as I've been testing DynamoDB Streams 
integration. In fact works with latest KCL 1.6.1 also which I was using.




So theKCL version does seem like it could be the issue - somewhere along the 
line an exception must be getting swallowed. Though the tests should have 
picked this up? Will dig deeper.




—
Sent from Mailbox

On Thu, Dec 10, 2015 at 11:07 PM, Brian London 
wrote:

> Yes, it worked in the 1.6 branch as of commit
> db5165246f2888537dd0f3d4c5a515875c7358ed.  That makes it much less serious
> of an issue, although it would be nice to know what the root cause is to
> avoid a regression.
> On Thu, Dec 10, 2015 at 4:03 PM Burak Yavuz  wrote:
>> I've noticed this happening when there was some dependency conflicts, and
>> it is super hard to debug.
>> It seems that the KinesisClientLibrary version in Spark 1.5.2 is 1.3.0,
>> but it is 1.2.1 in Spark 1.5.1.
>> I feel like that seems to be the problem...
>>
>> Brian, did you verify that it works with the 1.6.0 branch?
>>
>> Thanks,
>> Burak
>>
>> On Thu, Dec 10, 2015 at 11:45 AM, Brian London 
>> wrote:
>>
>>> Nick's symptoms sound identical to mine.  I should mention that I just
>>> pulled the latest version from github and it seems to be working there.  To
>>> reproduce:
>>>
>>>
>>>1. Download spark 1.5.2 from http://spark.apache.org/downloads.html
>>>2. build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.6.0 -DskipTests
>>>clean package
>>>3. build/mvn -Pkinesis-asl -DskipTests clean package
>>>4. Then run simultaneously:
>>>1. bin/run-example streaming.KinesisWordCountASL [Kinesis app name]
>>>   [Kinesis stream name] [endpoint URL]
>>>   2.   bin/run-example streaming.KinesisWordProducerASL [Kinesis
>>>   stream name] [endpoint URL] 100 10
>>>
>>>
>>> On Thu, Dec 10, 2015 at 2:05 PM Jean-Baptiste Onofré 
>>> wrote:
>>>
 Hi Nick,

 Just to be sure: don't you see some ClassCastException in the log ?

 Thanks,
 Regards
 JB

 On 12/10/2015 07:56 PM, Nick Pentreath wrote:
 > Could you provide an example / test case and more detail on what issue
 > you're facing?
 >
 > I've just tested a simple program reading from a dev Kinesis stream and
 > using stream.print() to show the records, and it works under 1.5.1 but
 > doesn't appear to be working under 1.5.2.
 >
 > UI for 1.5.2:
 >
 > Inline image 1
 >
 > UI for 1.5.1:
 >
 > Inline image 2
 >
 > On Thu, Dec 10, 2015 at 5:50 PM, Brian London >>> > > wrote:
 >
 > Has anyone managed to run the Kinesis demo in Spark 1.5.2?  The
 > Kinesis ASL that ships with 1.5.2 appears to not work for me
 > although 1.5.1 is fine. I spent some time with Amazon earlier in
 the
 > week and the only thing we could do to make it work is to change
 the
 > version to 1.5.1.  Can someone please attempt to reproduce before I
 > open a JIRA issue for it?
 >
 >

 --
 Jean-Baptiste Onofré
 jbono...@apache.org
 http://blog.nanthrax.net
 Talend - http://www.talend.com

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


>>

Re: Spark streaming with Kinesis broken?

[Brian London]

Yes, it worked in the 1.6 branch as of commit
db5165246f2888537dd0f3d4c5a515875c7358ed.  That makes it much less serious
of an issue, although it would be nice to know what the root cause is to
avoid a regression.

On Thu, Dec 10, 2015 at 4:03 PM Burak Yavuz  wrote:

> I've noticed this happening when there was some dependency conflicts, and
> it is super hard to debug.
> It seems that the KinesisClientLibrary version in Spark 1.5.2 is 1.3.0,
> but it is 1.2.1 in Spark 1.5.1.
> I feel like that seems to be the problem...
>
> Brian, did you verify that it works with the 1.6.0 branch?
>
> Thanks,
> Burak
>
> On Thu, Dec 10, 2015 at 11:45 AM, Brian London 
> wrote:
>
>> Nick's symptoms sound identical to mine.  I should mention that I just
>> pulled the latest version from github and it seems to be working there.  To
>> reproduce:
>>
>>
>>1. Download spark 1.5.2 from http://spark.apache.org/downloads.html
>>2. build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.6.0 -DskipTests
>>clean package
>>3. build/mvn -Pkinesis-asl -DskipTests clean package
>>4. Then run simultaneously:
>>1. bin/run-example streaming.KinesisWordCountASL [Kinesis app name]
>>   [Kinesis stream name] [endpoint URL]
>>   2.   bin/run-example streaming.KinesisWordProducerASL [Kinesis
>>   stream name] [endpoint URL] 100 10
>>
>>
>> On Thu, Dec 10, 2015 at 2:05 PM Jean-Baptiste Onofré 
>> wrote:
>>
>>> Hi Nick,
>>>
>>> Just to be sure: don't you see some ClassCastException in the log ?
>>>
>>> Thanks,
>>> Regards
>>> JB
>>>
>>> On 12/10/2015 07:56 PM, Nick Pentreath wrote:
>>> > Could you provide an example / test case and more detail on what issue
>>> > you're facing?
>>> >
>>> > I've just tested a simple program reading from a dev Kinesis stream and
>>> > using stream.print() to show the records, and it works under 1.5.1 but
>>> > doesn't appear to be working under 1.5.2.
>>> >
>>> > UI for 1.5.2:
>>> >
>>> > Inline image 1
>>> >
>>> > UI for 1.5.1:
>>> >
>>> > Inline image 2
>>> >
>>> > On Thu, Dec 10, 2015 at 5:50 PM, Brian London >> > > wrote:
>>> >
>>> > Has anyone managed to run the Kinesis demo in Spark 1.5.2?  The
>>> > Kinesis ASL that ships with 1.5.2 appears to not work for me
>>> > although 1.5.1 is fine. I spent some time with Amazon earlier in
>>> the
>>> > week and the only thing we could do to make it work is to change
>>> the
>>> > version to 1.5.1.  Can someone please attempt to reproduce before I
>>> > open a JIRA issue for it?
>>> >
>>> >
>>>
>>> --
>>> Jean-Baptiste Onofré
>>> jbono...@apache.org
>>> http://blog.nanthrax.net
>>> Talend - http://www.talend.com
>>>
>>> -
>>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
>>> For additional commands, e-mail: user-h...@spark.apache.org
>>>
>>>
>

Re: Spark streaming with Kinesis broken?

[Burak Yavuz]

I've noticed this happening when there was some dependency conflicts, and
it is super hard to debug.
It seems that the KinesisClientLibrary version in Spark 1.5.2 is 1.3.0, but
it is 1.2.1 in Spark 1.5.1.
I feel like that seems to be the problem...

Brian, did you verify that it works with the 1.6.0 branch?

Thanks,
Burak

On Thu, Dec 10, 2015 at 11:45 AM, Brian London 
wrote:

> Nick's symptoms sound identical to mine.  I should mention that I just
> pulled the latest version from github and it seems to be working there.  To
> reproduce:
>
>
>1. Download spark 1.5.2 from http://spark.apache.org/downloads.html
>2. build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.6.0 -DskipTests
>clean package
>3. build/mvn -Pkinesis-asl -DskipTests clean package
>4. Then run simultaneously:
>1. bin/run-example streaming.KinesisWordCountASL [Kinesis app name]
>   [Kinesis stream name] [endpoint URL]
>   2.   bin/run-example streaming.KinesisWordProducerASL [Kinesis
>   stream name] [endpoint URL] 100 10
>
>
> On Thu, Dec 10, 2015 at 2:05 PM Jean-Baptiste Onofré 
> wrote:
>
>> Hi Nick,
>>
>> Just to be sure: don't you see some ClassCastException in the log ?
>>
>> Thanks,
>> Regards
>> JB
>>
>> On 12/10/2015 07:56 PM, Nick Pentreath wrote:
>> > Could you provide an example / test case and more detail on what issue
>> > you're facing?
>> >
>> > I've just tested a simple program reading from a dev Kinesis stream and
>> > using stream.print() to show the records, and it works under 1.5.1 but
>> > doesn't appear to be working under 1.5.2.
>> >
>> > UI for 1.5.2:
>> >
>> > Inline image 1
>> >
>> > UI for 1.5.1:
>> >
>> > Inline image 2
>> >
>> > On Thu, Dec 10, 2015 at 5:50 PM, Brian London > > > wrote:
>> >
>> > Has anyone managed to run the Kinesis demo in Spark 1.5.2?  The
>> > Kinesis ASL that ships with 1.5.2 appears to not work for me
>> > although 1.5.1 is fine. I spent some time with Amazon earlier in the
>> > week and the only thing we could do to make it work is to change the
>> > version to 1.5.1.  Can someone please attempt to reproduce before I
>> > open a JIRA issue for it?
>> >
>> >
>>
>> --
>> Jean-Baptiste Onofré
>> jbono...@apache.org
>> http://blog.nanthrax.net
>> Talend - http://www.talend.com
>>
>> -
>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
>> For additional commands, e-mail: user-h...@spark.apache.org
>>
>>

Re: Spark streaming with Kinesis broken?

[Brian London]

Nick's symptoms sound identical to mine.  I should mention that I just
pulled the latest version from github and it seems to be working there.  To
reproduce:


   1. Download spark 1.5.2 from http://spark.apache.org/downloads.html
   2. build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.6.0 -DskipTests
   clean package
   3. build/mvn -Pkinesis-asl -DskipTests clean package
   4. Then run simultaneously:
   1. bin/run-example streaming.KinesisWordCountASL [Kinesis app name]
  [Kinesis stream name] [endpoint URL]
  2.   bin/run-example streaming.KinesisWordProducerASL [Kinesis stream
  name] [endpoint URL] 100 10


On Thu, Dec 10, 2015 at 2:05 PM Jean-Baptiste Onofré 
wrote:

> Hi Nick,
>
> Just to be sure: don't you see some ClassCastException in the log ?
>
> Thanks,
> Regards
> JB
>
> On 12/10/2015 07:56 PM, Nick Pentreath wrote:
> > Could you provide an example / test case and more detail on what issue
> > you're facing?
> >
> > I've just tested a simple program reading from a dev Kinesis stream and
> > using stream.print() to show the records, and it works under 1.5.1 but
> > doesn't appear to be working under 1.5.2.
> >
> > UI for 1.5.2:
> >
> > Inline image 1
> >
> > UI for 1.5.1:
> >
> > Inline image 2
> >
> > On Thu, Dec 10, 2015 at 5:50 PM, Brian London  > > wrote:
> >
> > Has anyone managed to run the Kinesis demo in Spark 1.5.2?  The
> > Kinesis ASL that ships with 1.5.2 appears to not work for me
> > although 1.5.1 is fine. I spent some time with Amazon earlier in the
> > week and the only thing we could do to make it work is to change the
> > version to 1.5.1.  Can someone please attempt to reproduce before I
> > open a JIRA issue for it?
> >
> >
>
> --
> Jean-Baptiste Onofré
> jbono...@apache.org
> http://blog.nanthrax.net
> Talend - http://www.talend.com
>
> -
> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
> For additional commands, e-mail: user-h...@spark.apache.org
>
>

Re: Spark streaming with Kinesis broken?

[Jean-Baptiste Onofré]

Hi Nick,

Just to be sure: don't you see some ClassCastException in the log ?

Thanks,
Regards
JB

On 12/10/2015 07:56 PM, Nick Pentreath wrote:

Could you provide an example / test case and more detail on what issue
you're facing?

I've just tested a simple program reading from a dev Kinesis stream and
using stream.print() to show the records, and it works under 1.5.1 but
doesn't appear to be working under 1.5.2.

UI for 1.5.2:

Inline image 1

UI for 1.5.1:

Inline image 2

On Thu, Dec 10, 2015 at 5:50 PM, Brian London mailto:brianmlon...@gmail.com>> wrote:

Has anyone managed to run the Kinesis demo in Spark 1.5.2?  The
Kinesis ASL that ships with 1.5.2 appears to not work for me
although 1.5.1 is fine. I spent some time with Amazon earlier in the
week and the only thing we could do to make it work is to change the
version to 1.5.1.  Can someone please attempt to reproduce before I
open a JIRA issue for it?




--
Jean-Baptiste Onofré
jbono...@apache.org
http://blog.nanthrax.net
Talend - http://www.talend.com

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

Spark streaming with Kinesis broken?

[Brian London]

Has anyone managed to run the Kinesis demo in Spark 1.5.2?  The Kinesis ASL
that ships with 1.5.2 appears to not work for me although 1.5.1 is fine. I
spent some time with Amazon earlier in the week and the only thing we could
do to make it work is to change the version to 1.5.1.  Can someone please
attempt to reproduce before I open a JIRA issue for it?

Re: Having problem with Spark streaming with Kinesis

[Ashrafuzzaman]

Thanks Aniket , clears a lot of confusion. 😄
On Dec 14, 2014 7:11 PM, "Aniket Bhatnagar" 
wrote:

> The reason is because of the following code:
>
> val numStreams = numShards
> val kinesisStreams = (0 until numStreams).map { i =>
>   KinesisUtils.createStream(ssc, streamName, endpointUrl,
> kinesisCheckpointInterval,
>   InitialPositionInStream.LATEST, StorageLevel.MEMORY_AND_DISK_2)
> }
>
> In the above code, numStreams is set as numShards. This enforces the need
> to have #shards + 1 workers. If you set numStreams as Math.min(numShards,
> numAvailableWorkers - 1), you can have lesser number of workers than number
> of shards. Makes sense?
>
> On Sun Dec 14 2014 at 10:06:36 A.K.M. Ashrafuzzaman <
> ashrafuzzaman...@gmail.com> wrote:
>
>> Thanks Aniket,
>> The trick is to have the #workers >= #shards + 1. But I don’t know why is
>> that.
>> http://spark.apache.org/docs/latest/streaming-kinesis-integration.html
>>
>> Here in the figure[spark streaming kinesis architecture], it seems like
>> one node should be able to take on more than one shards.
>>
>>
>> A.K.M. Ashrafuzzaman
>> Lead Software Engineer
>> NewsCred 
>>
>> (M) 880-175-5592433
>> Twitter  | Blog
>>  | Facebook
>> 
>>
>> Check out The Academy , your #1 source
>> for free content marketing resources
>>
>> On Nov 26, 2014, at 6:23 PM, A.K.M. Ashrafuzzaman <
>> ashrafuzzaman...@gmail.com> wrote:
>>
>> Hi guys,
>> When we are using Kinesis with 1 shard then it works fine. But when we
>> use more that 1 then it falls into an infinite loop and no data is
>> processed by the spark streaming. In the kinesis dynamo DB, I can see that
>> it keeps increasing the leaseCounter. But it do start processing.
>>
>> I am using,
>> scala: 2.10.4
>> java version: 1.8.0_25
>> Spark: 1.1.0
>> spark-streaming-kinesis-asl: 1.1.0
>>
>> A.K.M. Ashrafuzzaman
>> Lead Software Engineer
>> NewsCred 
>>
>> (M) 880-175-5592433
>> Twitter  | Blog
>>  | Facebook
>> 
>>
>> Check out The Academy , your #1 source
>> for free content marketing resources
>>
>>
>>

Re: Having problem with Spark streaming with Kinesis

[Aniket Bhatnagar]

The reason is because of the following code:

val numStreams = numShards
val kinesisStreams = (0 until numStreams).map { i =>
  KinesisUtils.createStream(ssc, streamName, endpointUrl,
kinesisCheckpointInterval,
  InitialPositionInStream.LATEST, StorageLevel.MEMORY_AND_DISK_2)
}

In the above code, numStreams is set as numShards. This enforces the need
to have #shards + 1 workers. If you set numStreams as Math.min(numShards,
numAvailableWorkers - 1), you can have lesser number of workers than number
of shards. Makes sense?

On Sun Dec 14 2014 at 10:06:36 A.K.M. Ashrafuzzaman <
ashrafuzzaman...@gmail.com> wrote:

> Thanks Aniket,
> The trick is to have the #workers >= #shards + 1. But I don’t know why is
> that.
> http://spark.apache.org/docs/latest/streaming-kinesis-integration.html
>
> Here in the figure[spark streaming kinesis architecture], it seems like
> one node should be able to take on more than one shards.
>
>
> A.K.M. Ashrafuzzaman
> Lead Software Engineer
> NewsCred 
>
> (M) 880-175-5592433
> Twitter  | Blog
>  | Facebook
> 
>
> Check out The Academy , your #1 source
> for free content marketing resources
>
> On Nov 26, 2014, at 6:23 PM, A.K.M. Ashrafuzzaman <
> ashrafuzzaman...@gmail.com> wrote:
>
> Hi guys,
> When we are using Kinesis with 1 shard then it works fine. But when we use
> more that 1 then it falls into an infinite loop and no data is processed by
> the spark streaming. In the kinesis dynamo DB, I can see that it keeps
> increasing the leaseCounter. But it do start processing.
>
> I am using,
> scala: 2.10.4
> java version: 1.8.0_25
> Spark: 1.1.0
> spark-streaming-kinesis-asl: 1.1.0
>
> A.K.M. Ashrafuzzaman
> Lead Software Engineer
> NewsCred 
>
> (M) 880-175-5592433
> Twitter  | Blog
>  | Facebook
> 
>
> Check out The Academy , your #1 source
> for free content marketing resources
>
>
>

Re: Having problem with Spark streaming with Kinesis

[A.K.M. Ashrafuzzaman]

Thanks Aniket,
The trick is to have the #workers >= #shards + 1. But I don’t know why is that.
http://spark.apache.org/docs/latest/streaming-kinesis-integration.html

Here in the figure[spark streaming kinesis architecture], it seems like one 
node should be able to take on more than one shards.


A.K.M. Ashrafuzzaman
Lead Software Engineer
NewsCred

(M) 880-175-5592433
Twitter | Blog | Facebook

Check out The Academy, your #1 source
for free content marketing resources

On Nov 26, 2014, at 6:23 PM, A.K.M. Ashrafuzzaman  
wrote:

> Hi guys,
> When we are using Kinesis with 1 shard then it works fine. But when we use 
> more that 1 then it falls into an infinite loop and no data is processed by 
> the spark streaming. In the kinesis dynamo DB, I can see that it keeps 
> increasing the leaseCounter. But it do start processing.
> 
> I am using,
> scala: 2.10.4
> java version: 1.8.0_25
> Spark: 1.1.0
> spark-streaming-kinesis-asl: 1.1.0
> 
> A.K.M. Ashrafuzzaman
> Lead Software Engineer
> NewsCred
> 
> (M) 880-175-5592433
> Twitter | Blog | Facebook
> 
> Check out The Academy, your #1 source
> for free content marketing resources
> 

Re: Having problem with Spark streaming with Kinesis

[A.K.M. Ashrafuzzaman]

Guys,
In my local machine it consumes a stream of Kinesis with 3 shards. But in EC2 
it does not consume from the stream. Later we found that the EC2 machine was of 
2 cores and my local machine was of 4 cores. I am using a single machine and in 
spark standalone mode. And we got a larger machine from EC2 and now the kinesis 
is getting consumed.

4 cores Single machine -> works
2 cores Single machine -> does not work
2 cores 2 workers -> does not work

So my question is that do we need a cluster of (#KinesisShards + 1) workers to 
be able to consume from Kinesis?


A.K.M. Ashrafuzzaman
Lead Software Engineer
NewsCred

(M) 880-175-5592433
Twitter | Blog | Facebook

Check out The Academy, your #1 source
for free content marketing resources

On Nov 27, 2014, at 10:28 AM, Aniket Bhatnagar  
wrote:

> Did you set spark master as local[*]? If so, then it means that nunber of 
> executors is equal to number of cores of the machine. Perhaps your mac 
> machine has more cores (certainly more than number of kinesis shards +1).
> 
> Try explicitly setting master as local[N] where N is number of kinesis shards 
> + 1. It should then work on both the machines.
> 
> On Thu, Nov 27, 2014, 9:46 AM Ashrafuzzaman  
> wrote:
> I was trying in one machine with just sbt run.
> 
> And it is working with my mac environment with the same configuration.
> 
> I used the sample code from 
> https://github.com/apache/spark/blob/master/extras/kinesis-asl/src/main/scala/org/apache/spark/examples/streaming/KinesisWordCountASL.scala
> 
> 
> val kinesisClient = new AmazonKinesisClient(new 
> DefaultAWSCredentialsProviderChain())
> kinesisClient.setEndpoint(endpointUrl)
> val numShards = 
> kinesisClient.describeStream(streamName).getStreamDescription().getShards()
>   .size()
> 
> /* In this example, we're going to create 1 Kinesis Worker/Receiver/DStream 
> for each shard. */
> val numStreams = numShards
> 
> /* Setup the and SparkConfig and StreamingContext */
> /* Spark Streaming batch interval */
> val batchInterval = Milliseconds(2000)
> val sparkConfig = new SparkConf().setAppName("KinesisWordCount")
> val ssc = new StreamingContext(sparkConfig, batchInterval)
> 
> /* Kinesis checkpoint interval.  Same as batchInterval for this example. */
> val kinesisCheckpointInterval = batchInterval
> 
> /* Create the same number of Kinesis DStreams/Receivers as Kinesis stream's 
> shards */
> val kinesisStreams = (0 until numStreams).map { i =>
>   KinesisUtils.createStream(ssc, streamName, endpointUrl, 
> kinesisCheckpointInterval,
>   InitialPositionInStream.LATEST, StorageLevel.MEMORY_AND_DISK_2)
> }
> 
> /* Union all the streams */
> val unionStreams = ssc.union(kinesisStreams)
> 
> /* Convert each line of Array[Byte] to String, split into words, and count 
> them */
> val words = unionStreams.flatMap(byteArray => new String(byteArray)
>   .split(" "))
> 
> /* Map each word to a (word, 1) tuple so we can reduce/aggregate by key. */
> val wordCounts = words.map(word => (word, 1)).reduceByKey(_ + _)
> 
> /* Print the first 10 wordCounts */
> wordCounts.print()
> 
> /* Start the streaming context and await termination */
> ssc.start()
> ssc.awaitTermination()
> 
> 
> 
> A.K.M. Ashrafuzzaman
> Lead Software Engineer
> NewsCred
> 
> (M) 880-175-5592433
> Twitter | Blog | Facebook
> 
> Check out The Academy, your #1 source
> for free content marketing resources
> 
> On Wed, Nov 26, 2014 at 11:26 PM, Aniket Bhatnagar 
>  wrote:
> What's your cluster size? For streamig to work, it needs shards + 1 executors.
> 
> On Wed, Nov 26, 2014, 5:53 PM A.K.M. Ashrafuzzaman 
>  wrote:
> Hi guys,
> When we are using Kinesis with 1 shard then it works fine. But when we use 
> more that 1 then it falls into an infinite loop and no data is processed by 
> the spark streaming. In the kinesis dynamo DB, I can see that it keeps 
> increasing the leaseCounter. But it do start processing.
> 
> I am using,
> scala: 2.10.4
> java version: 1.8.0_25
> Spark: 1.1.0
> spark-streaming-kinesis-asl: 1.1.0
> 
> A.K.M. Ashrafuzzaman
> Lead Software Engineer
> NewsCred
> 
> (M) 880-175-5592433
> Twitter | Blog | Facebook
> 
> Check out The Academy, your #1 source
> for free content marketing resources
> 
> 

Re: Having problem with Spark streaming with Kinesis

[Aniket Bhatnagar]

Did you set spark master as local[*]? If so, then it means that nunber of
executors is equal to number of cores of the machine. Perhaps your mac
machine has more cores (certainly more than number of kinesis shards +1).

Try explicitly setting master as local[N] where N is number of kinesis
shards + 1. It should then work on both the machines.

On Thu, Nov 27, 2014, 9:46 AM Ashrafuzzaman 
wrote:

> I was trying in one machine with just sbt run.
>
> And it is working with my mac environment with the same configuration.
>
> I used the sample code from
> https://github.com/apache/spark/blob/master/extras/kinesis-asl/src/main/scala/org/apache/spark/examples/streaming/KinesisWordCountASL.scala
>
>
> val kinesisClient = new AmazonKinesisClient(new
> DefaultAWSCredentialsProviderChain())
> kinesisClient.setEndpoint(endpointUrl)
> val numShards =
> kinesisClient.describeStream(streamName).getStreamDescription().getShards()
>   .size()
>
> /* In this example, we're going to create 1 Kinesis
> Worker/Receiver/DStream for each shard. */
> val numStreams = numShards
>
> /* Setup the and SparkConfig and StreamingContext */
> /* Spark Streaming batch interval */
> val batchInterval = Milliseconds(2000)
> val sparkConfig = new SparkConf().setAppName("KinesisWordCount")
> val ssc = new StreamingContext(sparkConfig, batchInterval)
>
> /* Kinesis checkpoint interval.  Same as batchInterval for this example. */
> val kinesisCheckpointInterval = batchInterval
>
> /* Create the same number of Kinesis DStreams/Receivers as Kinesis
> stream's shards */
> val kinesisStreams = (0 until numStreams).map { i =>
>   KinesisUtils.createStream(ssc, streamName, endpointUrl,
> kinesisCheckpointInterval,
>   InitialPositionInStream.LATEST, StorageLevel.MEMORY_AND_DISK_2)
> }
>
> /* Union all the streams */
> val unionStreams = ssc.union(kinesisStreams)
>
> /* Convert each line of Array[Byte] to String, split into words, and count
> them */
> val words = unionStreams.flatMap(byteArray => new String(byteArray)
>   .split(" "))
>
> /* Map each word to a (word, 1) tuple so we can reduce/aggregate by key. */
> val wordCounts = words.map(word => (word, 1)).reduceByKey(_ + _)
>
> /* Print the first 10 wordCounts */
> wordCounts.print()
>
> /* Start the streaming context and await termination */
> ssc.start()
> ssc.awaitTermination()
>
>
>
> A.K.M. Ashrafuzzaman
> Lead Software Engineer
> NewsCred 
>
> (M) 880-175-5592433
> Twitter  | Blog
>  | Facebook
> 
>
> Check out The Academy , your #1 source
> for free content marketing resources
>
> On Wed, Nov 26, 2014 at 11:26 PM, Aniket Bhatnagar <
> aniket.bhatna...@gmail.com> wrote:
>
>> What's your cluster size? For streamig to work, it needs shards + 1
>> executors.
>>
>> On Wed, Nov 26, 2014, 5:53 PM A.K.M. Ashrafuzzaman <
>> ashrafuzzaman...@gmail.com> wrote:
>>
>>> Hi guys,
>>> When we are using Kinesis with 1 shard then it works fine. But when we
>>> use more that 1 then it falls into an infinite loop and no data is
>>> processed by the spark streaming. In the kinesis dynamo DB, I can see that
>>> it keeps increasing the leaseCounter. But it do start processing.
>>>
>>> I am using,
>>> scala: 2.10.4
>>> java version: 1.8.0_25
>>> Spark: 1.1.0
>>> spark-streaming-kinesis-asl: 1.1.0
>>>
>>> A.K.M. Ashrafuzzaman
>>> Lead Software Engineer
>>> NewsCred 
>>>
>>> (M) 880-175-5592433
>>> Twitter  | Blog
>>>  | Facebook
>>> 
>>>
>>> Check out The Academy , your #1 source
>>> for free content marketing resources
>>>
>>>
>

Re: Having problem with Spark streaming with Kinesis

[Ashrafuzzaman]

I was trying in one machine with just sbt run.

And it is working with my mac environment with the same configuration.

I used the sample code from
https://github.com/apache/spark/blob/master/extras/kinesis-asl/src/main/scala/org/apache/spark/examples/streaming/KinesisWordCountASL.scala


val kinesisClient = new AmazonKinesisClient(new
DefaultAWSCredentialsProviderChain())
kinesisClient.setEndpoint(endpointUrl)
val numShards =
kinesisClient.describeStream(streamName).getStreamDescription().getShards()
  .size()

/* In this example, we're going to create 1 Kinesis Worker/Receiver/DStream
for each shard. */
val numStreams = numShards

/* Setup the and SparkConfig and StreamingContext */
/* Spark Streaming batch interval */
val batchInterval = Milliseconds(2000)
val sparkConfig = new SparkConf().setAppName("KinesisWordCount")
val ssc = new StreamingContext(sparkConfig, batchInterval)

/* Kinesis checkpoint interval.  Same as batchInterval for this example. */
val kinesisCheckpointInterval = batchInterval

/* Create the same number of Kinesis DStreams/Receivers as Kinesis stream's
shards */
val kinesisStreams = (0 until numStreams).map { i =>
  KinesisUtils.createStream(ssc, streamName, endpointUrl,
kinesisCheckpointInterval,
  InitialPositionInStream.LATEST, StorageLevel.MEMORY_AND_DISK_2)
}

/* Union all the streams */
val unionStreams = ssc.union(kinesisStreams)

/* Convert each line of Array[Byte] to String, split into words, and count
them */
val words = unionStreams.flatMap(byteArray => new String(byteArray)
  .split(" "))

/* Map each word to a (word, 1) tuple so we can reduce/aggregate by key. */
val wordCounts = words.map(word => (word, 1)).reduceByKey(_ + _)

/* Print the first 10 wordCounts */
wordCounts.print()

/* Start the streaming context and await termination */
ssc.start()
ssc.awaitTermination()



A.K.M. Ashrafuzzaman
Lead Software Engineer
NewsCred 

(M) 880-175-5592433
Twitter  | Blog
 | Facebook


Check out The Academy , your #1 source
for free content marketing resources

On Wed, Nov 26, 2014 at 11:26 PM, Aniket Bhatnagar <
aniket.bhatna...@gmail.com> wrote:

> What's your cluster size? For streamig to work, it needs shards + 1
> executors.
>
> On Wed, Nov 26, 2014, 5:53 PM A.K.M. Ashrafuzzaman <
> ashrafuzzaman...@gmail.com> wrote:
>
>> Hi guys,
>> When we are using Kinesis with 1 shard then it works fine. But when we
>> use more that 1 then it falls into an infinite loop and no data is
>> processed by the spark streaming. In the kinesis dynamo DB, I can see that
>> it keeps increasing the leaseCounter. But it do start processing.
>>
>> I am using,
>> scala: 2.10.4
>> java version: 1.8.0_25
>> Spark: 1.1.0
>> spark-streaming-kinesis-asl: 1.1.0
>>
>> A.K.M. Ashrafuzzaman
>> Lead Software Engineer
>> NewsCred 
>>
>> (M) 880-175-5592433
>> Twitter  | Blog
>>  | Facebook
>> 
>>
>> Check out The Academy , your #1 source
>> for free content marketing resources
>>
>>

Re: Having problem with Spark streaming with Kinesis

[Aniket Bhatnagar]

What's your cluster size? For streamig to work, it needs shards + 1
executors.

On Wed, Nov 26, 2014, 5:53 PM A.K.M. Ashrafuzzaman <
ashrafuzzaman...@gmail.com> wrote:

> Hi guys,
> When we are using Kinesis with 1 shard then it works fine. But when we use
> more that 1 then it falls into an infinite loop and no data is processed by
> the spark streaming. In the kinesis dynamo DB, I can see that it keeps
> increasing the leaseCounter. But it do start processing.
>
> I am using,
> scala: 2.10.4
> java version: 1.8.0_25
> Spark: 1.1.0
> spark-streaming-kinesis-asl: 1.1.0
>
> A.K.M. Ashrafuzzaman
> Lead Software Engineer
> NewsCred 
>
> (M) 880-175-5592433
> Twitter  | Blog
>  | Facebook
> 
>
> Check out The Academy , your #1 source
> for free content marketing resources
>
>

Re: Having problem with Spark streaming with Kinesis

[Akhil Das]

I have it working without any issues (tried with 5 shrads), except my java
version was 1.7.

Here's the piece of code that i used.

  System.setProperty("AWS_ACCESS_KEY_ID",
this.kConf.getOrElse("access_key", ""))
System.setProperty("AWS_SECRET_KEY", this.kConf.getOrElse("secret",
""))  val streamName = this.kConf.getOrElse("stream", "")  val
endpointUrl = 
this.kConf.getOrElse("end_point","https://kinesis.us-east-1.amazonaws.com/";)
 val kinesisClient = new AmazonKinesisClient(new
DefaultAWSCredentialsProviderChain())
kinesisClient.setEndpoint(endpointUrl)  *val numShards =
kinesisClient.describeStream(streamName).getStreamDescription().getShards()
.size()*  val numStreams = numShards  val
kinesisCheckpointInterval = Seconds(this.kConf.getOrElse("duration",
"").toInt)  val kinesisStreams = (0 until numStreams).map { i =>
 KinesisUtils.createStream(ssc, streamName, endpointUrl,
kinesisCheckpointInterval,  InitialPositionInStream.LATEST,
StorageLevel.MEMORY_AND_DISK_2)  }  /* Union all the streams
*/  val unionStreams = ssc.union(kinesisStreams)  val
tmp_stream = unionStreams.map(byteArray => new String(byteArray))

  tmp_stream.print()




Thanks
Best Regards

On Wed, Nov 26, 2014 at 5:53 PM, A.K.M. Ashrafuzzaman <
ashrafuzzaman...@gmail.com> wrote:

> Hi guys,
> When we are using Kinesis with 1 shard then it works fine. But when we use
> more that 1 then it falls into an infinite loop and no data is processed by
> the spark streaming. In the kinesis dynamo DB, I can see that it keeps
> increasing the leaseCounter. But it do start processing.
>
> I am using,
> scala: 2.10.4
> java version: 1.8.0_25
> Spark: 1.1.0
> spark-streaming-kinesis-asl: 1.1.0
>
> A.K.M. Ashrafuzzaman
> Lead Software Engineer
> NewsCred 
>
> (M) 880-175-5592433
> Twitter  | Blog
>  | Facebook
> 
>
> Check out The Academy , your #1 source
> for free content marketing resources
>
>

Having problem with Spark streaming with Kinesis

[A.K.M. Ashrafuzzaman]

Hi guys,
When we are using Kinesis with 1 shard then it works fine. But when we use more 
that 1 then it falls into an infinite loop and no data is processed by the 
spark streaming. In the kinesis dynamo DB, I can see that it keeps increasing 
the leaseCounter. But it do start processing.

I am using,
scala: 2.10.4
java version: 1.8.0_25
Spark: 1.1.0
spark-streaming-kinesis-asl: 1.1.0

A.K.M. Ashrafuzzaman
Lead Software Engineer
NewsCred

(M) 880-175-5592433
Twitter | Blog | Facebook

Check out The Academy, your #1 source
for free content marketing resources

Re: Spark Streaming with Kinesis

[Matt Chu]

I haven't tried this myself yet, but this sounds relevant:

https://github.com/apache/spark/pull/2535

Will be giving this a try today or so, will report back.

On Wednesday, October 29, 2014, Harold Nguyen  wrote:

> Hi again,
>
> After getting through several dependencies, I finally got to this
> non-dependency type error:
>
> Exception in thread "main" java.lang.NoSuchMethodError:
> org.apache.http.impl.conn.DefaultClientConnectionOperator.(Lorg/apache/http/conn/scheme/SchemeRegistry;Lorg/apache/http/conn/DnsResolver;)V
>
> It look every similar to this post:
>
>
> http://stackoverflow.com/questions/24788949/nosuchmethoderror-while-running-aws-s3-client-on-spark-while-javap-shows-otherwi
>
> Since I'm a little new to everything, would someone be able to provide a
> step-by-step guidance for that ?
>
> Harold
>
> On Wed, Oct 29, 2014 at 9:22 AM, Harold Nguyen  > wrote:
>
>> Hi all,
>>
>> I followed the guide here:
>> http://spark.apache.org/docs/latest/streaming-kinesis-integration.html
>>
>> But got this error:
>> Exception in thread "main" java.lang.NoClassDefFoundError:
>> com/amazonaws/auth/AWSCredentialsProvider
>>
>> Would you happen to know what dependency or jar is needed ?
>>
>> Harold
>>
>>
>

Re: Spark Streaming with Kinesis

[Harold Nguyen]

Hi again,

After getting through several dependencies, I finally got to this
non-dependency type error:

Exception in thread "main" java.lang.NoSuchMethodError:
org.apache.http.impl.conn.DefaultClientConnectionOperator.(Lorg/apache/http/conn/scheme/SchemeRegistry;Lorg/apache/http/conn/DnsResolver;)V

It look every similar to this post:

http://stackoverflow.com/questions/24788949/nosuchmethoderror-while-running-aws-s3-client-on-spark-while-javap-shows-otherwi

Since I'm a little new to everything, would someone be able to provide a
step-by-step guidance for that ?

Harold

On Wed, Oct 29, 2014 at 9:22 AM, Harold Nguyen  wrote:

> Hi all,
>
> I followed the guide here:
> http://spark.apache.org/docs/latest/streaming-kinesis-integration.html
>
> But got this error:
> Exception in thread "main" java.lang.NoClassDefFoundError:
> com/amazonaws/auth/AWSCredentialsProvider
>
> Would you happen to know what dependency or jar is needed ?
>
> Harold
>
>

Spark Streaming with Kinesis

[Harold Nguyen]

Hi all,

I followed the guide here:
http://spark.apache.org/docs/latest/streaming-kinesis-integration.html

But got this error:
Exception in thread "main" java.lang.NoClassDefFoundError:
com/amazonaws/auth/AWSCredentialsProvider

Would you happen to know what dependency or jar is needed ?

Harold