Collector.collect

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Collector.collect

gaurav
Hello 

I am working on RichProcessFunction and I want to emit multiple records at a time. To achieve this, I am currently doing :

while(condition)
{
   Collector.collect(new Tuple<>...);
}

I was wondering, is this the correct way or there is any other alternative. 


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RE: Collector.collect

Newport, Billy

We’ve done that but it’s very expensive from a serialization point of view when writing the same record multiple times, each in a different tuple.

 

For example, we started with this:

 

.collect(new Tuple<Short, GenericRecord)).

 

The record would be written with short = 0 and again with short = 1. This results in the GenericRecord being serialized twice. You also prolly need filters on the output dataset which is expensive also.

 

We switched instead to a bitmask. Now, we write the record once and set bits in the short for each file the record needs to be written to. Our next step is to write records to a file based on the short. We wrote a new outputrecordformat which checks the bits in the short and writes the GenericRecord to each file for the corresponding bit. This means no filter to split the records for each file and this is much faster.

 

We’re finding a need to do this kind of optimization pretty frequently with flink.

 

 

From: Gaurav Khandelwal [mailto:[hidden email]]
Sent: Saturday, April 29, 2017 4:32 AM
To: [hidden email]
Subject: Collector.collect

 

Hello 

 

I am working on RichProcessFunction and I want to emit multiple records at a time. To achieve this, I am currently doing :

 

while(condition)

{

   Collector.collect(new Tuple<>...);

}

 

I was wondering, is this the correct way or there is any other alternative. 

 

 

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Re: Collector.collect

Chesnay Schepler
Hello,

@Billy, what prevented you from duplicating/splitting the record, based on the bitmask, in a map function before the sink?
This shouldn't incur any serialization overhead if the sink is chained to the map. The emitted Tuple could also share the
GenericRecord; meaning you don't even have to copy it.

On 01.05.2017 14:52, Newport, Billy wrote:

We’ve done that but it’s very expensive from a serialization point of view when writing the same record multiple times, each in a different tuple.

 

For example, we started with this:

 

.collect(new Tuple<Short, GenericRecord)).

 

The record would be written with short = 0 and again with short = 1. This results in the GenericRecord being serialized twice. You also prolly need filters on the output dataset which is expensive also.

 

We switched instead to a bitmask. Now, we write the record once and set bits in the short for each file the record needs to be written to. Our next step is to write records to a file based on the short. We wrote a new outputrecordformat which checks the bits in the short and writes the GenericRecord to each file for the corresponding bit. This means no filter to split the records for each file and this is much faster.

 

We’re finding a need to do this kind of optimization pretty frequently with flink.

 

 

From: Gaurav Khandelwal [[hidden email]]
Sent: Saturday, April 29, 2017 4:32 AM
To: [hidden email]
Subject: Collector.collect

 

Hello 

 

I am working on RichProcessFunction and I want to emit multiple records at a time. To achieve this, I am currently doing :

 

while(condition)

{

   Collector.collect(new Tuple<>...);

}

 

I was wondering, is this the correct way or there is any other alternative. 

 

 


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RE: Collector.collect

Newport, Billy

There is likely a bug then, the ENUM,Record stream to a filter to a set of outputformats per filter was slower than the BITMASK,Record to single OutputFormat which demux’s the data to each file internally

 

Are you saying do a custom writer inside a map rather than either of the 2 above approaches?

 

 

From: Chesnay Schepler [mailto:[hidden email]]
Sent: Monday, May 01, 2017 10:41 AM
To: [hidden email]
Subject: Re: Collector.collect

 

Hello,

@Billy, what prevented you from duplicating/splitting the record, based on the bitmask, in a map function before the sink?
This shouldn't incur any serialization overhead if the sink is chained to the map. The emitted Tuple could also share the
GenericRecord; meaning you don't even have to copy it.

On 01.05.2017 14:52, Newport, Billy wrote:

We’ve done that but it’s very expensive from a serialization point of view when writing the same record multiple times, each in a different tuple.

 

For example, we started with this:

 

.collect(new Tuple<Short, GenericRecord)).

 

The record would be written with short = 0 and again with short = 1. This results in the GenericRecord being serialized twice. You also prolly need filters on the output dataset which is expensive also.

 

We switched instead to a bitmask. Now, we write the record once and set bits in the short for each file the record needs to be written to. Our next step is to write records to a file based on the short. We wrote a new outputrecordformat which checks the bits in the short and writes the GenericRecord to each file for the corresponding bit. This means no filter to split the records for each file and this is much faster.

 

We’re finding a need to do this kind of optimization pretty frequently with flink.

 

 

From: Gaurav Khandelwal [[hidden email]]
Sent: Saturday, April 29, 2017 4:32 AM
To: [hidden email]
Subject: Collector.collect

 

Hello 

 

I am working on RichProcessFunction and I want to emit multiple records at a time. To achieve this, I am currently doing :

 

while(condition)

{

   Collector.collect(new Tuple<>...);

}

 

I was wondering, is this the correct way or there is any other alternative. 

 

 

 

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Re: Collector.collect

Chesnay Schepler
Oh you have multiple different output formats, missed that.

For the Batch API you are i believe correct, using a custom output-format is the best solution.

In the Streaming API the code below should be equally fast, if the filtered sets don't overlap.

input = ...
input.filter(conditionA).output(formatA)
input.filter(conditonB).output(formatB)

That is because all filters would be chained; hell all sources might be as well (not to sure on this one).

On 01.05.2017 17:05, Newport, Billy wrote:

There is likely a bug then, the ENUM,Record stream to a filter to a set of outputformats per filter was slower than the BITMASK,Record to single OutputFormat which demux’s the data to each file internally

 

Are you saying do a custom writer inside a map rather than either of the 2 above approaches?

 

 

From: Chesnay Schepler [[hidden email]]
Sent: Monday, May 01, 2017 10:41 AM
To: [hidden email]
Subject: Re: Collector.collect

 

Hello,

@Billy, what prevented you from duplicating/splitting the record, based on the bitmask, in a map function before the sink?
This shouldn't incur any serialization overhead if the sink is chained to the map. The emitted Tuple could also share the
GenericRecord; meaning you don't even have to copy it.

On 01.05.2017 14:52, Newport, Billy wrote:

We’ve done that but it’s very expensive from a serialization point of view when writing the same record multiple times, each in a different tuple.

 

For example, we started with this:

 

.collect(new Tuple<Short, GenericRecord)).

 

The record would be written with short = 0 and again with short = 1. This results in the GenericRecord being serialized twice. You also prolly need filters on the output dataset which is expensive also.

 

We switched instead to a bitmask. Now, we write the record once and set bits in the short for each file the record needs to be written to. Our next step is to write records to a file based on the short. We wrote a new outputrecordformat which checks the bits in the short and writes the GenericRecord to each file for the corresponding bit. This means no filter to split the records for each file and this is much faster.

 

We’re finding a need to do this kind of optimization pretty frequently with flink.

 

 

From: Gaurav Khandelwal [[hidden email]]
Sent: Saturday, April 29, 2017 4:32 AM
To: [hidden email]
Subject: Collector.collect

 

Hello 

 

I am working on RichProcessFunction and I want to emit multiple records at a time. To achieve this, I am currently doing :

 

while(condition)

{

   Collector.collect(new Tuple<>...);

}

 

I was wondering, is this the correct way or there is any other alternative. 

 

 

 


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RE: Collector.collect

Newport, Billy

Why doesn’t this work with batch though. We did

 

input = ...
input.filter(conditionA).output(formatA)
input.filter(conditonB).output(formatB)

 

And it was pretty slow compared with a custom outputformat with an integrated filter.

 

 

From: Chesnay Schepler [mailto:[hidden email]]
Sent: Monday, May 01, 2017 12:56 PM
To: Newport, Billy [Tech]; '[hidden email]'
Subject: Re: Collector.collect

 

Oh you have multiple different output formats, missed that.

For the Batch API you are i believe correct, using a custom output-format is the best solution.

In the Streaming API the code below should be equally fast, if the filtered sets don't overlap.

input = ...
input.filter(conditionA).output(formatA)
input.filter(conditonB).output(formatB)

That is because all filters would be chained; hell all sources might be as well (not to sure on this one).

On 01.05.2017 17:05, Newport, Billy wrote:

There is likely a bug then, the ENUM,Record stream to a filter to a set of outputformats per filter was slower than the BITMASK,Record to single OutputFormat which demux’s the data to each file internally

 

Are you saying do a custom writer inside a map rather than either of the 2 above approaches?

 

 

From: Chesnay Schepler [[hidden email]]
Sent: Monday, May 01, 2017 10:41 AM
To: [hidden email]
Subject: Re: Collector.collect

 

Hello,

@Billy, what prevented you from duplicating/splitting the record, based on the bitmask, in a map function before the sink?
This shouldn't incur any serialization overhead if the sink is chained to the map. The emitted Tuple could also share the
GenericRecord; meaning you don't even have to copy it.

On 01.05.2017 14:52, Newport, Billy wrote:

We’ve done that but it’s very expensive from a serialization point of view when writing the same record multiple times, each in a different tuple.

 

For example, we started with this:

 

.collect(new Tuple<Short, GenericRecord)).

 

The record would be written with short = 0 and again with short = 1. This results in the GenericRecord being serialized twice. You also prolly need filters on the output dataset which is expensive also.

 

We switched instead to a bitmask. Now, we write the record once and set bits in the short for each file the record needs to be written to. Our next step is to write records to a file based on the short. We wrote a new outputrecordformat which checks the bits in the short and writes the GenericRecord to each file for the corresponding bit. This means no filter to split the records for each file and this is much faster.

 

We’re finding a need to do this kind of optimization pretty frequently with flink.

 

 

From: Gaurav Khandelwal [[hidden email]]
Sent: Saturday, April 29, 2017 4:32 AM
To: [hidden email]
Subject: Collector.collect

 

Hello 

 

I am working on RichProcessFunction and I want to emit multiple records at a time. To achieve this, I am currently doing :

 

while(condition)

{

   Collector.collect(new Tuple<>...);

}

 

I was wondering, is this the correct way or there is any other alternative. 

 

 

 

 

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Re: Collector.collect

Chesnay Schepler
In the Batch API only a single operator can be chained to another operator.

So we're starting with this code:
input = ...
input.filter(conditionA).output(formatA)
input.filter(conditonB).output(formatB)
In the Batch API this would create a CHAIN(filterA -> formatA) and a CHAIN(filterB -> formatB), both having "input" as their input.
Since the filtering is not done as part of "input" the entire input DataSet must be sent to both tasks.
This means that both chains have to deserialize the entire DataSet to apply the filter; the serialization should only be done once though.

In contrast the solution you wrote creates a single CHAIN(input, format), with no serialization in between at all.

The Streaming API doesn't have this limitation and would get by without any serialization as well. Probably.

On 02.05.2017 15:23, Newport, Billy wrote:

Why doesn’t this work with batch though. We did

 

input = ...
input.filter(conditionA).output(formatA)
input.filter(conditonB).output(formatB)

 

And it was pretty slow compared with a custom outputformat with an integrated filter.

 

 

From: Chesnay Schepler [[hidden email]]
Sent: Monday, May 01, 2017 12:56 PM
To: Newport, Billy [Tech]; '[hidden email]'
Subject: Re: Collector.collect

 

Oh you have multiple different output formats, missed that.

For the Batch API you are i believe correct, using a custom output-format is the best solution.

In the Streaming API the code below should be equally fast, if the filtered sets don't overlap.

input = ...
input.filter(conditionA).output(formatA)
input.filter(conditonB).output(formatB)

That is because all filters would be chained; hell all sources might be as well (not to sure on this one).

On 01.05.2017 17:05, Newport, Billy wrote:

There is likely a bug then, the ENUM,Record stream to a filter to a set of outputformats per filter was slower than the BITMASK,Record to single OutputFormat which demux’s the data to each file internally

 

Are you saying do a custom writer inside a map rather than either of the 2 above approaches?

 

 

From: Chesnay Schepler [[hidden email]]
Sent: Monday, May 01, 2017 10:41 AM
To: [hidden email]
Subject: Re: Collector.collect

 

Hello,

@Billy, what prevented you from duplicating/splitting the record, based on the bitmask, in a map function before the sink?
This shouldn't incur any serialization overhead if the sink is chained to the map. The emitted Tuple could also share the
GenericRecord; meaning you don't even have to copy it.

On 01.05.2017 14:52, Newport, Billy wrote:

We’ve done that but it’s very expensive from a serialization point of view when writing the same record multiple times, each in a different tuple.

 

For example, we started with this:

 

.collect(new Tuple<Short, GenericRecord)).

 

The record would be written with short = 0 and again with short = 1. This results in the GenericRecord being serialized twice. You also prolly need filters on the output dataset which is expensive also.

 

We switched instead to a bitmask. Now, we write the record once and set bits in the short for each file the record needs to be written to. Our next step is to write records to a file based on the short. We wrote a new outputrecordformat which checks the bits in the short and writes the GenericRecord to each file for the corresponding bit. This means no filter to split the records for each file and this is much faster.

 

We’re finding a need to do this kind of optimization pretty frequently with flink.

 

 

From: Gaurav Khandelwal [[hidden email]]
Sent: Saturday, April 29, 2017 4:32 AM
To: [hidden email]
Subject: Collector.collect

 

Hello 

 

I am working on RichProcessFunction and I want to emit multiple records at a time. To achieve this, I am currently doing :

 

while(condition)

{

   Collector.collect(new Tuple<>...);

}

 

I was wondering, is this the correct way or there is any other alternative.