Stream reorder example. Issue #179 #411
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sshcherbakov
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Thanks for the PR @sshcherbakov looks good overall, I just have a couple of comments.
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| public class ReorderIntegrationTest { | ||
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| public static class ReorderTransfomer<K, V> |
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nit: spelling RecordTransfomer -> RecordTransformer
| * <p> | ||
| * Makes sense only on per partition basis. | ||
| * <p> | ||
| * Reordering occurs within time windows defined by the |
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nit: I think you meant to say "....defined by the provided grace
| */ | ||
| @Override | ||
| public KeyValue<K, V> transform(final K key, final V value) { | ||
| final long ts = timestampExtractor.getTimestamp(value); |
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This isn't used, unless you want to provide this for demo purposes - so maybe add a comment?
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The Kafka Streams TimestampExtractor could have been reused to illustrate pulling the timestamp from the payload, but the method signature is not convenient. Instead of duplicating TimestampExtractor interface with convenient signature removed removed this piece to reduce confusion.
| * @param timestamp – stream time of the punctuate function call | ||
| */ | ||
| void punctuate(final long timestamp) { | ||
| try(KeyValueIterator<K, V> it = reorderStore.all()) { |
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The comments state to use range(from, to), but the code uses all() since the code deletes everything in the store after forwarding, I think it will continue to work as-is, but you should update the comments.
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Rebased PR on top of the current master branch. I cannot build master but I checked the test with the latest release branch |
| try(KeyValueIterator<K, V> it = reorderStore.all()) { | ||
| while (it.hasNext()) { | ||
| final KeyValue<K, V> kv = it.next(); | ||
| context.forward(kv.key, kv.value); |
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I think this implementation is flawed. Ordering only makes sense per partition/key.
Say incoming records have key k1, and there are two messages with timestamps t0, and t1. The StoreKeyGenerator will map that into some combination of the original key and the record timestamp, say something simple like t0_k1 and t1_k1. However, when you forward these message with the "composite" store key, they'll likely end up in two different partitions. Hence, although you sorted them, any downstream processor/consumer has no guarantee in the order after the re-partition. The correct thing to do would be to preserve the original key, and use that to forward the message, while using the composite key to store/sort/dedup records.
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It is an example. It can be extended with either additional store for composite to original key mapping or a second interface that would allow extracting original key from the composite one before passing downstream.
| final K storeKey = storeKeyGenerator.getStoreKey(key, value); | ||
| final V storeValue = reorderStore.get(storeKey); | ||
| if(storeValue == null) { | ||
| reorderStore.put(storeKey, value); |
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Do you mean pitIfAbsent() is equivalent or it has different logic?
In its description: "Update the value associated with this key, unless a value is already associated with the key."
Before I start interpreting that and guessing whether it will only put my value where there is no key or even when key is there but the value is null, I write my intent explicitly through additional "if" line here.
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We are currently starting to migrate the examples in this repository to https://github.com/confluentinc/tutorials, so it didn't make sense to merge this here just to move it later. There is a PR now under review. As a result, I'm closing this PR now. \cc @mjsax , @sshcherbakov |
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Thank you @sshcherbakov for the awesome contribution! |
Example of reordering out of order messages using a stateful transformer.