Add documentation #4
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docs/conf.py
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Seems like these versions mismatch? major.minor should match, the remaining .patch-SNAPSHOT could possibly differ.
docs/elasticsearch_connector.rst
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| * **Batching and Pipelining**: The connector supports batching and pipelined writing to Elasticsearch. | ||
| It accumulates messages in batches and allows concurrent processing of multiple batches. | ||
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| * **Delivery Ordering**: When pipelining is turned off, the connector supports ordering of delivery |
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Why does this matter? Does Elastic maintain some kind of insert-order on docs? When would ordering of messages be useful? Perhaps you have an example you can illustrate with?
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@ewencp Add more docs. PTAL. Thanks! |
docs/elasticsearch_connector.rst
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| (`use cases <https://www.elastic.co/blog/found-uses-of-elasticsearch>`_). The connector covers | ||
| both the analytics and key-value store use cases. For the analytics use case, | ||
| each message is in Kafka is treated as an event and the connector uses ``topic+partition+offset`` | ||
| as unique identifiers for events, which then converted to unique documents in Elasticsearch. |
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as unique identifiers -> as a unique identifier
docs/elasticsearch_connector.rst
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| 1. The connector job that ingest data to the old indices continue writing to the old indices. | ||
| 2. Create a new connector job that writes to new indices. This will copy both some old data and | ||
| new data to the new indices as long as the data is in Kafka. | ||
| 4. Once the data in the old indices are moved to the new indices by the reindexing process, we |
Contributor
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@Ishiihara Looks good, there's a few cleanups but LGTM. |
sp-gupta
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Aug 6, 2024
sp-gupta
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Aug 6, 2024
Update eclipse parsson version (#4)
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