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https://issues.apache.org/jira/browse/BEAM-9008?focusedWorklogId=379781&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-379781
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ASF GitHub Bot logged work on BEAM-9008:
----------------------------------------
Author: ASF GitHub Bot
Created on: 31/Jan/20 07:33
Start Date: 31/Jan/20 07:33
Worklog Time Spent: 10m
Work Description: vmarquez commented on issue #10546: [BEAM-9008] Add
CassandraIO readAll method
URL: https://github.com/apache/beam/pull/10546#issuecomment-580619044
@iemejia I have started working on a different implementation of ReadAll
that extends `PTransform<PCollection<Read<T>>, PCollection<T>>`, however, I
have thought about it more and I am thinking that it is bad more undesireable
than we thought to *not* establish a connection in `setup` of the `ReadFn`
class. Just this week at work I had to do some work involving generating
hundreds of thousands of queries (`RingRanges`), and the vast majority of them
returned no or almost no data! The data was sparse and never the less I still
needed to perform the queries, so having to establish a new connection per
`RingRange` in the `processElement` method would have slown things down a lot.
I understand the desire to have simpler code, but I think the performance
impact would be noticable if we only keep connection information in the
`Read<T>` that comes into the `processElement` method. Do you still want to
proceed with that?
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Issue Time Tracking
-------------------
Worklog Id: (was: 379781)
Time Spent: 4.5h (was: 4h 20m)
> Add readAll() method to CassandraIO
> -----------------------------------
>
> Key: BEAM-9008
> URL: https://issues.apache.org/jira/browse/BEAM-9008
> Project: Beam
> Issue Type: New Feature
> Components: io-java-cassandra
> Affects Versions: 2.16.0
> Reporter: vincent marquez
> Assignee: vincent marquez
> Priority: Minor
> Time Spent: 4.5h
> Remaining Estimate: 0h
>
> When querying a large cassandra database, it's often *much* more useful to
> programatically generate the queries needed to to be run rather than reading
> all partitions and attempting some filtering.
> As an example:
> {code:java}
> public class Event {
> @PartitionKey(0) public UUID accountId;
> @PartitionKey(1)public String yearMonthDay;
> @ClusteringKey public UUID eventId;
> //other data...
> }{code}
> If there is ten years worth of data, you may want to only query one year's
> worth. Here each token range would represent one 'token' but all events for
> the day.
> {code:java}
> Set<UUID> accounts = getRelevantAccounts();
> Set<String> dateRange = generateDateRange("2018-01-01", "2019-01-01");
> PCollection<TokenRange> tokens = generateTokens(accounts, dateRange);
> {code}
>
> I propose an additional _readAll()_ PTransform that can take a PCollection
> of token ranges and can return a PCollection<T> of what the query would
> return.
> *Question: How much code should be in common between both methods?*
> Currently the read connector already groups all partitions into a List of
> Token Ranges, so it would be simple to refactor the current read() based
> method to a 'ParDo' based one and have them both share the same function.
> Reasons against sharing code between read and readAll
> * Not having the read based method return a BoundedSource connector would
> mean losing the ability to know the size of the data returned
> * Currently the CassandraReader executes all the grouped TokenRange queries
> *asynchronously* which is (maybe?) fine when all that's happening is
> splitting up all the partition ranges but terrible for executing potentially
> millions of queries.
> Reasons _for_ sharing code would be simplified code base and that both of
> the above issues would most likely have a negligable performance impact.
>
>
>
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