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### Description Add delta table connector and test against a delta table generated via delta.io and uploaded to s3. Shows an example of how to use the connection options to leverage s3. I was able to get this to work with s3 if I pass in the access and secret keys as storage options. Even though the s3 bucket being used is public, would not work without those. --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
112 lines
4.0 KiB
ReStructuredText
112 lines
4.0 KiB
ReStructuredText
Delta Table
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==========
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Connect delta tables to your preprocessing pipeline, and batch process all your records using ``unstructured-ingest`` to store structured outputs locally on your filesystem.
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First you'll need to install the delta table dependencies as shown here.
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.. code:: shell
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pip install "unstructured[delta-table]"
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Run Locally
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-----------
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.. tabs::
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.. tab:: Shell
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.. code:: shell
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unstructured-ingest \
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delta-table \
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--table-uri s3://utic-dev-tech-fixtures/sample-delta-lake-data/deltatable/ \
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--structured-output-dir delta-table-example \
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--storage_options "AWS_REGION=us-east-2,AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID,AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY" \
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--verbose
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.. tab:: Python
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.. code:: python
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import subprocess
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command = [
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"unstructured-ingest",
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"delta-table",
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"--table-uri", "s3://utic-dev-tech-fixtures/sample-delta-lake-data/deltatable/",
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"--download-dir", "delta-table-ingest-download",
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"--structured-output-dir", "delta-table-example",
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"--preserve-downloads",
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"--storage_options", "AWS_REGION=us-east-2,AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID,AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY",
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"--verbose",
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]
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# Run the command
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process = subprocess.Popen(command, stdout=subprocess.PIPE)
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output, error = process.communicate()
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# Print output
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if process.returncode == 0:
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print('Command executed successfully. Output:')
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print(output.decode())
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else:
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print('Command failed. Error:')
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print(error.decode())
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Run via the API
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---------------
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You can also use upstream connectors with the ``unstructured`` API. For this you'll need to use the ``--partition-by-api`` flag and pass in your API key with ``--api-key``.
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.. tabs::
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.. tab:: Shell
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.. code:: shell
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unstructured-ingest \
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delta-table \
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--table-uri s3://utic-dev-tech-fixtures/sample-delta-lake-data/deltatable/ \
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--structured-output-dir delta-table-example \
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--storage_options "AWS_REGION=us-east-2,AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID,AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY" \
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--verbose
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--partition-by-api \
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--api-key "<UNSTRUCTURED-API-KEY>"
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.. tab:: Python
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.. code:: python
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import subprocess
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command = [
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"unstructured-ingest",
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"delta-table",
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"--table-uri", "s3://utic-dev-tech-fixtures/sample-delta-lake-data/deltatable/",
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"--download-dir", "delta-table-ingest-download",
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"--structured-output-dir", "delta-table-example",
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"--preserve-downloads",
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"--storage_options", "AWS_REGION=us-east-2,AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID,AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY",
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"--verbose",
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"--partition-by-api",
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"--api-key", "<UNSTRUCTURED-API-KEY>",
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]
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# Run the command
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process = subprocess.Popen(command, stdout=subprocess.PIPE)
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output, error = process.communicate()
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# Print output
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if process.returncode == 0:
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print('Command executed successfully. Output:')
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print(output.decode())
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else:
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print('Command failed. Error:')
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print(error.decode())
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Additionally, you will need to pass the ``--partition-endpoint`` if you're running the API locally. You can find more information about the ``unstructured`` API `here <https://github.com/Unstructured-IO/unstructured-api>`_.
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For a full list of the options the CLI accepts check ``unstructured-ingest delta-table --help``.
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NOTE: Keep in mind that you will need to have all the appropriate extras and dependencies for the file types of the documents contained in your data storage platform if you're running this locally. You can find more information about this in the `installation guide <https://unstructured-io.github.io/unstructured/installing.html>`_.
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