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#162: Updated developer guide with staged commit behaviour #182

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Jul 7, 2023
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#162: Updated developer guide with staged commit behaviour #182

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Updated developer guide
morazow Jul 7, 2023
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morazow Jul 7, 2023
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3 changes: 3 additions & 0 deletions .gitignore
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Expand Up @@ -58,6 +58,9 @@ tmp
.project
.scala_dependencies
*.sc
**/.settings/org.eclipse.core.resources.prefs
**/.settings/org.eclipse.jdt.apt.core.prefs
**/.settings/org.eclipse.m2e.core.prefs

# Ensime
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18 changes: 18 additions & 0 deletions doc/development/developer_guide.md
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Expand Up @@ -14,6 +14,24 @@ userProvidedS3Bucket/

The generated intermediate write path `<UUID>-<SparkApplicationId>/<SparkQueryId>/` is validated that it is empty before write. And it is cleaned up after the write query finishes.

## S3 Staging Commit Process

The Spark job that writes data to Exasol uses an AWS S3 bucket as intermediate storage. In this process, the `ExasolS3Table` API implementation uses Spark [`CSVTable`](https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/csv/CSVTable.scala) writer to create files in S3.

The write process continues as following:

1. We ask Spark's `CSVTable` to commit data into S3 bucket
1. We commit to import this data into Exasol database using Exasol's `CSV` loader
1. And finally we ask our `ExasolS3Table` API implementation to commit the write process

If any failure occurs, each step will trigger the `abort` method and S3 bucket locations will be cleaned up. If job finishes successfully, the Spark job end listener will trigger the cleanup process.

## S3 Maximum Number of Files

For the write Spark jobs, we allow maximum of `1000` CSV files to be written as intermediate data into S3 bucket. The main reason for this is that S3 SDK `listObjects` command returns up to 1000 objects from a bucket path per each request.

Even though we could improve it to list more objects from S3 bucket with multiple requests, we wanted to keep this threshold for now.

## Integration Tests

The integration tests are run using [Docker](https://www.docker.com) and [exasol-testcontainers](https://github.com/exasol/exasol-testcontainers/)