DataSetUtils zipWithIndex question

[Tarandeep Singh]

Hi,

I am looking at implementation of zipWithIndex in DataSetUtils-
https://github.com/apache/flink/blob/master/flink-java/src/main/java/org/apache/flink/api/java/utils/DataSetUtils.java

It works in two phases/steps

1) Count number of elements in each partition (using mapPartition)

2) In second mapPartition, unique ID is assigned by calculating offset using number of elements computed in step 1.

Is there any chance the second mapPartition won't get same number of elements as first mapPartition (assuming data is in HDFS)?

Thanks

Tarandeep

[Till Rohrmann]

Hi Tarandeep,

the number of elements in each partition should stay constant. In fact the elements in each partition should not change.

Cheers,

Till

On Wed, Mar 30, 2016 at 8:14 AM, Tarandeep Singh <[hidden email]> wrote:

Hi,

I am looking at implementation of zipWithIndex in DataSetUtils-
https://github.com/apache/flink/blob/master/flink-java/src/main/java/org/apache/flink/api/java/utils/DataSetUtils.java

It works in two phases/steps

1) Count number of elements in each partition (using mapPartition)

2) In second mapPartition, unique ID is assigned by calculating offset using number of elements computed in step 1.

Is there any chance the second mapPartition won't get same number of elements as first mapPartition (assuming data is in HDFS)?

Thanks

Tarandeep

[Flavio Pompermaier]

Hi Till and Tarandeep,

I'm also interested in better understanding my knowledge about the concept of a partition..

From what I know a partition is the portion of data assigned by the job manager to each task manager..right?

Then, each partition is divided again at the task manager to maximize the slot usage..is it correct?

In every case, there will be a case where at least one partition is smaller than the others...am I wrong? Am I confusing some term..?

Best,

Flavio

On Thu, Mar 31, 2016 at 1:56 PM, Till Rohrmann <[hidden email]> wrote:

Hi Tarandeep,

the number of elements in each partition should stay constant. In fact the elements in each partition should not change.

Cheers,

Till

On Wed, Mar 30, 2016 at 8:14 AM, Tarandeep Singh <[hidden email]> wrote:

Hi,

I am looking at implementation of zipWithIndex in DataSetUtils-
https://github.com/apache/flink/blob/master/flink-java/src/main/java/org/apache/flink/api/java/utils/DataSetUtils.java

It works in two phases/steps

1) Count number of elements in each partition (using mapPartition)

2) In second mapPartition, unique ID is assigned by calculating offset using number of elements computed in step 1.

Is there any chance the second mapPartition won't get same number of elements as first mapPartition (assuming data is in HDFS)?

Thanks

Tarandeep

[Till Rohrmann]

A partition is the portion of data each task receives. Thus, the degree of parallelism of your program/task decides how many different partitions you have. Depending on the upstream operators (and which data is send to which task), the partitions will most likely differ in size.

Cheers,

Till

On Thu, Mar 31, 2016 at 2:11 PM, Flavio Pompermaier <[hidden email]> wrote:

Hi Till and Tarandeep,

I'm also interested in better understanding my knowledge about the concept of a partition..

From what I know a partition is the portion of data assigned by the job manager to each task manager..right?

Then, each partition is divided again at the task manager to maximize the slot usage..is it correct?

In every case, there will be a case where at least one partition is smaller than the others...am I wrong? Am I confusing some term..?

Best,

Flavio

On Thu, Mar 31, 2016 at 1:56 PM, Till Rohrmann <[hidden email]> wrote:

Hi Tarandeep,

the number of elements in each partition should stay constant. In fact the elements in each partition should not change.

Cheers,

Till

On Wed, Mar 30, 2016 at 8:14 AM, Tarandeep Singh <[hidden email]> wrote:

Hi,

I am looking at implementation of zipWithIndex in DataSetUtils-
https://github.com/apache/flink/blob/master/flink-java/src/main/java/org/apache/flink/api/java/utils/DataSetUtils.java

It works in two phases/steps

1) Count number of elements in each partition (using mapPartition)

2) In second mapPartition, unique ID is assigned by calculating offset using number of elements computed in step 1.

Is there any chance the second mapPartition won't get same number of elements as first mapPartition (assuming data is in HDFS)?

Thanks

Tarandeep

[Flavio Pompermaier]

Ok, thanks for the clarification Till!

On Thu, Mar 31, 2016 at 2:14 PM, Till Rohrmann <[hidden email]> wrote:

A partition is the portion of data each task receives. Thus, the degree of parallelism of your program/task decides how many different partitions you have. Depending on the upstream operators (and which data is send to which task), the partitions will most likely differ in size.

Cheers,

Till

On Thu, Mar 31, 2016 at 2:11 PM, Flavio Pompermaier <[hidden email]> wrote:

Hi Till and Tarandeep,

I'm also interested in better understanding my knowledge about the concept of a partition..

From what I know a partition is the portion of data assigned by the job manager to each task manager..right?

Then, each partition is divided again at the task manager to maximize the slot usage..is it correct?

In every case, there will be a case where at least one partition is smaller than the others...am I wrong? Am I confusing some term..?

Best,

Flavio

On Thu, Mar 31, 2016 at 1:56 PM, Till Rohrmann <[hidden email]> wrote:

Hi Tarandeep,

the number of elements in each partition should stay constant. In fact the elements in each partition should not change.

Cheers,

Till

On Wed, Mar 30, 2016 at 8:14 AM, Tarandeep Singh <[hidden email]> wrote:

Hi,

I am looking at implementation of zipWithIndex in DataSetUtils-
https://github.com/apache/flink/blob/master/flink-java/src/main/java/org/apache/flink/api/java/utils/DataSetUtils.java

It works in two phases/steps

1) Count number of elements in each partition (using mapPartition)

2) In second mapPartition, unique ID is assigned by calculating offset using number of elements computed in step 1.

Is there any chance the second mapPartition won't get same number of elements as first mapPartition (assuming data is in HDFS)?

Thanks

Tarandeep