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https://github.com/Unstructured-IO/unstructured.git
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fd293b3e78
Closes https://github.com/Unstructured-IO/unstructured/issues/1842
Closes https://github.com/Unstructured-IO/unstructured/issues/2202
Closes https://github.com/Unstructured-IO/unstructured/issues/2203
This PR:
- Adds Elasticsearch destination connector to be able to ingest
documents from any supported source, embed them and write the embeddings
/ documents into Elasticsearch.
- Defines an example unstructured elements schema for users to be able
to setup their unstructured elasticsearch indexes easily.
- Includes parallelized upload and lazy processing for elasticsearch
destination connector.
- Rearranges elasticsearch test helpers to source, destination, and
common folders.
- Adds util functions to be able to batch iterables in a lazy way for
uploads
- Fixes a bug where removing the optional parameter `--fields` broke the
connector due to an integer processing error.
- Fixes a bug where using an [elasticsearch
config](8fa5cbf036/unstructured/ingest/connector/elasticsearch.py (L26-L35))
for a destination connector resulted in a serialization issue when
optional parameter `--fields` was not provided.
38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
import os
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DATA_PATH = "scripts/elasticsearch-test-helpers/source_connector/wiki_movie_plots_small.csv"
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CLUSTER_URL = "http://localhost:9200"
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INDEX_NAME = "movies"
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USER = os.environ["ELASTIC_USER"]
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PASSWORD = os.environ["ELASTIC_PASSWORD"]
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MAPPINGS = {
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"properties": {
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"title": {"type": "text", "analyzer": "english"},
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"ethnicity": {"type": "text", "analyzer": "standard"},
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"director": {"type": "text", "analyzer": "standard"},
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"cast": {"type": "text", "analyzer": "standard"},
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"genre": {"type": "text", "analyzer": "standard"},
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"plot": {"type": "text", "analyzer": "english"},
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"year": {"type": "integer"},
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"wiki_page": {"type": "keyword"},
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},
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}
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def form_elasticsearch_doc_dict(i, csv_row):
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return {
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"_index": INDEX_NAME,
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"_id": i,
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"_source": {
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"title": csv_row["Title"],
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"ethnicity": csv_row["Origin/Ethnicity"],
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"director": csv_row["Director"],
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"cast": csv_row["Cast"],
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"genre": csv_row["Genre"],
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"plot": csv_row["Plot"],
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"year": csv_row["Release Year"],
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"wiki_page": csv_row["Wiki Page"],
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},
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}
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