Async cassandra queries

I've been trying to update an app to enhance performance, it uses Datastax Cassandra Java Driver for DAL services.

Now, I need to convert sync queries to async queries, I didn't find satisfactory answers to my doubts (at least not on the web pages I visited).

Could anybody please answer the below queries or refer to a link where I could get an answer.

1> What are the possible problematic scenarios I need to worry about before changing synced executes to ansync execs?

2> How will reads and writes behave, can I change one of them without worrying about any issues?

Thanks in advance!

edited Nov 12 '18 at 18:59

Alex Ott

27.3k35072

asked Nov 12 '18 at 8:50

Kumar Kavish

123

Asyn queries references: 1) datastax.com/dev/blog/java-driver-async-queries 2) docs.datastax.com/en/developer/java-driver/3.6/manual/async

– abpan
Nov 12 '18 at 14:16

add a comment |

I've been trying to update an app to enhance performance, it uses Datastax Cassandra Java Driver for DAL services.

Now, I need to convert sync queries to async queries, I didn't find satisfactory answers to my doubts (at least not on the web pages I visited).

Could anybody please answer the below queries or refer to a link where I could get an answer.

1> What are the possible problematic scenarios I need to worry about before changing synced executes to ansync execs?

2> How will reads and writes behave, can I change one of them without worrying about any issues?

Thanks in advance!

edited Nov 12 '18 at 18:59

Alex Ott

27.3k35072

asked Nov 12 '18 at 8:50

Kumar Kavish

123

Asyn queries references: 1) datastax.com/dev/blog/java-driver-async-queries 2) docs.datastax.com/en/developer/java-driver/3.6/manual/async

– abpan
Nov 12 '18 at 14:16

add a comment |

I've been trying to update an app to enhance performance, it uses Datastax Cassandra Java Driver for DAL services.

Now, I need to convert sync queries to async queries, I didn't find satisfactory answers to my doubts (at least not on the web pages I visited).

Could anybody please answer the below queries or refer to a link where I could get an answer.

1> What are the possible problematic scenarios I need to worry about before changing synced executes to ansync execs?

2> How will reads and writes behave, can I change one of them without worrying about any issues?

Thanks in advance!

edited Nov 12 '18 at 18:59

Alex Ott

27.3k35072

asked Nov 12 '18 at 8:50

Kumar Kavish

123

I've been trying to update an app to enhance performance, it uses Datastax Cassandra Java Driver for DAL services.

Now, I need to convert sync queries to async queries, I didn't find satisfactory answers to my doubts (at least not on the web pages I visited).

Could anybody please answer the below queries or refer to a link where I could get an answer.

1> What are the possible problematic scenarios I need to worry about before changing synced executes to ansync execs?

2> How will reads and writes behave, can I change one of them without worrying about any issues?

Thanks in advance!

asynchronous cassandra cassandra-2.0 datastax-java-driver

edited Nov 12 '18 at 18:59

Alex Ott

27.3k35072

asked Nov 12 '18 at 8:50

Kumar Kavish

123

edited Nov 12 '18 at 18:59

Alex Ott

27.3k35072

asked Nov 12 '18 at 8:50

Kumar Kavish

123

edited Nov 12 '18 at 18:59

Alex Ott

27.3k35072

edited Nov 12 '18 at 18:59

Alex Ott

27.3k35072

edited Nov 12 '18 at 18:59

Alex Ott

27.3k35072

asked Nov 12 '18 at 8:50

Kumar Kavish

123

asked Nov 12 '18 at 8:50

Kumar Kavish

123

asked Nov 12 '18 at 8:50

Kumar Kavish

123

Asyn queries references: 1) datastax.com/dev/blog/java-driver-async-queries 2) docs.datastax.com/en/developer/java-driver/3.6/manual/async

– abpan
Nov 12 '18 at 14:16

add a comment |

Asyn queries references: 1) datastax.com/dev/blog/java-driver-async-queries 2) docs.datastax.com/en/developer/java-driver/3.6/manual/async

– abpan
Nov 12 '18 at 14:16

Asyn queries references: 1) datastax.com/dev/blog/java-driver-async-queries 2) docs.datastax.com/en/developer/java-driver/3.6/manual/async

– abpan
Nov 12 '18 at 14:16

add a comment |

1 Answer
1

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votes

There are several things that you need to think about:

You need to rate limit your code - by default it's only 1024 request per connection, so you may need to increase this number. But even with increased number of request per connection it's easy to overload Cassandra, so you still need to control it, with something like this;

You need correctly handle errors - you may need to add error handler to promise that is returned, and react correspondingly;

You need correctly create statements - for example, don't reuse the same BoundStatement as it's not thread safe;

don't re-use same List/Set/Map instances that you pass as parameters, etc.

answered Nov 12 '18 at 10:14

Alex Ott

27.3k35072

Thanks Alex, one more thing, how exactly does pairing batch statements with executeAsync work, given that batches maintain atomicity. Can I combine them to get a better performance without losing atomicity?

– Kumar Kavish
Nov 20 '18 at 9:04

there are different types of batches - you can batch for multiple tables, you can batch for same table, etc. If you batch for same partition inside table, then it's much faster than sending the same queries multiple times. But otherwise, use of batches with executeAsync is the same as with execute...

– Alex Ott
Nov 20 '18 at 9:11

great! made it perfectly clear, well in my case the batch is for multiple tables, so I think using executeAsync is useless.

– Kumar Kavish
Nov 20 '18 at 9:38

Why, it's still useful, as you can still parallelize execution, without adding more threads. But you really need to think about use of batches - they are quite expensive, and should be used only in limited amount of cases

– Alex Ott
Nov 20 '18 at 9:40

Using batches to ensure the atomicity of the transaction. The initial code that I wrote was to process the batch in async fashion. I have multiple transactions, each with a set of upserts. So, rather than executing batch for each of them in a synced manner, I am trying to use async with each batch to get better performance. Makes sense, right?

– Kumar Kavish
Nov 20 '18 at 9:49

|
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There are several things that you need to think about:

You need to rate limit your code - by default it's only 1024 request per connection, so you may need to increase this number. But even with increased number of request per connection it's easy to overload Cassandra, so you still need to control it, with something like this;

You need correctly handle errors - you may need to add error handler to promise that is returned, and react correspondingly;

You need correctly create statements - for example, don't reuse the same BoundStatement as it's not thread safe;

don't re-use same List/Set/Map instances that you pass as parameters, etc.

answered Nov 12 '18 at 10:14

Alex Ott

27.3k35072

Thanks Alex, one more thing, how exactly does pairing batch statements with executeAsync work, given that batches maintain atomicity. Can I combine them to get a better performance without losing atomicity?

– Kumar Kavish
Nov 20 '18 at 9:04

there are different types of batches - you can batch for multiple tables, you can batch for same table, etc. If you batch for same partition inside table, then it's much faster than sending the same queries multiple times. But otherwise, use of batches with executeAsync is the same as with execute...

– Alex Ott
Nov 20 '18 at 9:11

great! made it perfectly clear, well in my case the batch is for multiple tables, so I think using executeAsync is useless.

– Kumar Kavish
Nov 20 '18 at 9:38

Why, it's still useful, as you can still parallelize execution, without adding more threads. But you really need to think about use of batches - they are quite expensive, and should be used only in limited amount of cases

– Alex Ott
Nov 20 '18 at 9:40

Using batches to ensure the atomicity of the transaction. The initial code that I wrote was to process the batch in async fashion. I have multiple transactions, each with a set of upserts. So, rather than executing batch for each of them in a synced manner, I am trying to use async with each batch to get better performance. Makes sense, right?

– Kumar Kavish
Nov 20 '18 at 9:49

|
show 2 more comments

There are several things that you need to think about:

You need to rate limit your code - by default it's only 1024 request per connection, so you may need to increase this number. But even with increased number of request per connection it's easy to overload Cassandra, so you still need to control it, with something like this;

You need correctly handle errors - you may need to add error handler to promise that is returned, and react correspondingly;

You need correctly create statements - for example, don't reuse the same BoundStatement as it's not thread safe;

don't re-use same List/Set/Map instances that you pass as parameters, etc.

answered Nov 12 '18 at 10:14

Alex Ott

27.3k35072

Thanks Alex, one more thing, how exactly does pairing batch statements with executeAsync work, given that batches maintain atomicity. Can I combine them to get a better performance without losing atomicity?

– Kumar Kavish
Nov 20 '18 at 9:04

there are different types of batches - you can batch for multiple tables, you can batch for same table, etc. If you batch for same partition inside table, then it's much faster than sending the same queries multiple times. But otherwise, use of batches with executeAsync is the same as with execute...

– Alex Ott
Nov 20 '18 at 9:11

great! made it perfectly clear, well in my case the batch is for multiple tables, so I think using executeAsync is useless.

– Kumar Kavish
Nov 20 '18 at 9:38

Why, it's still useful, as you can still parallelize execution, without adding more threads. But you really need to think about use of batches - they are quite expensive, and should be used only in limited amount of cases

– Alex Ott
Nov 20 '18 at 9:40

Using batches to ensure the atomicity of the transaction. The initial code that I wrote was to process the batch in async fashion. I have multiple transactions, each with a set of upserts. So, rather than executing batch for each of them in a synced manner, I am trying to use async with each batch to get better performance. Makes sense, right?

– Kumar Kavish
Nov 20 '18 at 9:49

|
show 2 more comments

There are several things that you need to think about:

You need to rate limit your code - by default it's only 1024 request per connection, so you may need to increase this number. But even with increased number of request per connection it's easy to overload Cassandra, so you still need to control it, with something like this;

You need correctly handle errors - you may need to add error handler to promise that is returned, and react correspondingly;

You need correctly create statements - for example, don't reuse the same BoundStatement as it's not thread safe;

don't re-use same List/Set/Map instances that you pass as parameters, etc.

answered Nov 12 '18 at 10:14

Alex Ott

27.3k35072

There are several things that you need to think about:

You need to rate limit your code - by default it's only 1024 request per connection, so you may need to increase this number. But even with increased number of request per connection it's easy to overload Cassandra, so you still need to control it, with something like this;

You need correctly handle errors - you may need to add error handler to promise that is returned, and react correspondingly;

You need correctly create statements - for example, don't reuse the same BoundStatement as it's not thread safe;

don't re-use same List/Set/Map instances that you pass as parameters, etc.

answered Nov 12 '18 at 10:14

Alex Ott

27.3k35072

answered Nov 12 '18 at 10:14

Alex Ott

27.3k35072

answered Nov 12 '18 at 10:14

Alex Ott

27.3k35072

answered Nov 12 '18 at 10:14

Alex Ott

27.3k35072

Thanks Alex, one more thing, how exactly does pairing batch statements with executeAsync work, given that batches maintain atomicity. Can I combine them to get a better performance without losing atomicity?

– Kumar Kavish
Nov 20 '18 at 9:04

there are different types of batches - you can batch for multiple tables, you can batch for same table, etc. If you batch for same partition inside table, then it's much faster than sending the same queries multiple times. But otherwise, use of batches with executeAsync is the same as with execute...

– Alex Ott
Nov 20 '18 at 9:11

great! made it perfectly clear, well in my case the batch is for multiple tables, so I think using executeAsync is useless.

– Kumar Kavish
Nov 20 '18 at 9:38

Why, it's still useful, as you can still parallelize execution, without adding more threads. But you really need to think about use of batches - they are quite expensive, and should be used only in limited amount of cases

– Alex Ott
Nov 20 '18 at 9:40

Using batches to ensure the atomicity of the transaction. The initial code that I wrote was to process the batch in async fashion. I have multiple transactions, each with a set of upserts. So, rather than executing batch for each of them in a synced manner, I am trying to use async with each batch to get better performance. Makes sense, right?

– Kumar Kavish
Nov 20 '18 at 9:49

|
show 2 more comments

Thanks Alex, one more thing, how exactly does pairing batch statements with executeAsync work, given that batches maintain atomicity. Can I combine them to get a better performance without losing atomicity?

– Kumar Kavish
Nov 20 '18 at 9:04

there are different types of batches - you can batch for multiple tables, you can batch for same table, etc. If you batch for same partition inside table, then it's much faster than sending the same queries multiple times. But otherwise, use of batches with executeAsync is the same as with execute...

– Alex Ott
Nov 20 '18 at 9:11

great! made it perfectly clear, well in my case the batch is for multiple tables, so I think using executeAsync is useless.

– Kumar Kavish
Nov 20 '18 at 9:38

Why, it's still useful, as you can still parallelize execution, without adding more threads. But you really need to think about use of batches - they are quite expensive, and should be used only in limited amount of cases

– Alex Ott
Nov 20 '18 at 9:40

Using batches to ensure the atomicity of the transaction. The initial code that I wrote was to process the batch in async fashion. I have multiple transactions, each with a set of upserts. So, rather than executing batch for each of them in a synced manner, I am trying to use async with each batch to get better performance. Makes sense, right?

– Kumar Kavish
Nov 20 '18 at 9:49

Thanks Alex, one more thing, how exactly does pairing batch statements with executeAsync work, given that batches maintain atomicity. Can I combine them to get a better performance without losing atomicity?

– Kumar Kavish
Nov 20 '18 at 9:04

there are different types of batches - you can batch for multiple tables, you can batch for same table, etc. If you batch for same partition inside table, then it's much faster than sending the same queries multiple times. But otherwise, use of batches with executeAsync is the same as with execute...

– Alex Ott
Nov 20 '18 at 9:11

great! made it perfectly clear, well in my case the batch is for multiple tables, so I think using executeAsync is useless.

– Kumar Kavish
Nov 20 '18 at 9:38

Why, it's still useful, as you can still parallelize execution, without adding more threads. But you really need to think about use of batches - they are quite expensive, and should be used only in limited amount of cases

– Alex Ott
Nov 20 '18 at 9:40

Using batches to ensure the atomicity of the transaction. The initial code that I wrote was to process the batch in async fashion. I have multiple transactions, each with a set of upserts. So, rather than executing batch for each of them in a synced manner, I am trying to use async with each batch to get better performance. Makes sense, right?

– Kumar Kavish
Nov 20 '18 at 9:49

|
show 2 more comments

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