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https://issues.apache.org/jira/browse/BEAM-9008?focusedWorklogId=376934&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-376934
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ASF GitHub Bot logged work on BEAM-9008:
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Author: ASF GitHub Bot
Created on: 24/Jan/20 17:35
Start Date: 24/Jan/20 17:35
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-577996918
@iemejia I think that could work, thanks for your patience as I try to
understand what you're thinking. Some questions:
1. If our `ReadFn<A> extends DoFn<Read<A>, A>` and the only way we have
connection information is from the `Read<A>` passed in to the processElement,
that means we need to re-establish a DB connection for each batch of queries
we run? As in, the connection would be established in the `processElement`
method and could not be in `setup` method?
2. How would that work for the end user of a
`PTransform<PCollection<Read<A>, PCollection<A>>`? Here is what I did in the
test and would wand to document how end users could generate 'queries',
https://github.com/apache/beam/pull/10546/files#diff-8ba4ea3b09d563a67e29ff8584269d35R499
Would we instead want to return a `PCollection<Read<A>>` by using something
like `return CassandraIO.read().withRingRange(new RingRange(start, finish))`?
If we do that however, we'd need to do the `withHosts` and all the other
connection information, no? The other option is establishing one `ReadAll`
PTransform that maps over the `Read<A>` input and enriches the db connection
information?
3. Originally I had wanted to have the ReadFn operate on a *collection* of
'query' objects to ensure a way to enforce linearizability with our queries
(mainly so we don't oversaturate a single node/shard). Currently the groupBy
function a user passes in operates on the `RingRange` object, would we keep it
that way and just, under the hood, allow for a single `Read<A>` to hold a
collection of RingRanges?
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Issue Time Tracking
-------------------
Worklog Id: (was: 376934)
Time Spent: 3h 50m (was: 3h 40m)
> 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: 3h 50m
> 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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