parquet reader implementation as a new input type

.semversioner/next-release/patch-20260409021555501931.json

@@ -0,0 +1,4 @@
+{
+  "type": "patch",
+  "description": "implement parquet reader"
+}

packages/graphrag-input/graphrag_input/input_reader_factory.py

@@ -81,6 +81,10 @@ def create_input_reader(config: InputConfig, storage: Storage) -> InputReader:
                 from graphrag_input.markitdown import MarkItDownFileReader
 
                 register_input_reader(InputType.MarkItDown, MarkItDownFileReader)
+            case InputType.Parquet:
+                from graphrag_input.parquet import ParquetFileReader
+
+                register_input_reader(InputType.Parquet, ParquetFileReader)
             case _:
                 msg = f"InputConfig.type '{input_strategy}' is not registered in the InputReaderFactory. Registered types: {', '.join(input_reader_factory.keys())}."
                 raise ValueError(msg)

packages/graphrag-input/graphrag_input/input_type.py

@@ -19,6 +19,8 @@ class InputType(StrEnum):
     """The JSON Lines input type."""
     MarkItDown = "markitdown"
     """The MarkItDown input type."""
+    Parquet = "parquet"
+    """The Parquet input type."""
 
     def __repr__(self):
         """Get a string representation."""

packages/graphrag-input/graphrag_input/parquet.py

@@ -0,0 +1,39 @@
+# Copyright (c) 2024 Microsoft Corporation.
+# Licensed under the MIT License
+
+"""A module containing 'ParquetFileReader' model."""
+
+import io
+import logging
+
+import pyarrow.parquet as pq
+
+from graphrag_input.structured_file_reader import StructuredFileReader
+from graphrag_input.text_document import TextDocument
+
+logger = logging.getLogger(__name__)
+
+
+class ParquetFileReader(StructuredFileReader):
+    """Reader implementation for parquet files."""
+
+    def __init__(self, file_pattern: str | None = None, **kwargs):
+        super().__init__(
+            file_pattern=file_pattern if file_pattern is not None else ".*\\.parquet$",
+            **kwargs,
+        )
+
+    async def read_file(self, path: str) -> list[TextDocument]:
+        """Read a parquet file into a list of documents.
+
+        Args:
+            - path - The path to read the file from.
+
+        Returns
+        -------
+            - output - list with a TextDocument for each row in the file.
+        """
+        file_bytes = await self._storage.get(path, as_bytes=True)
+        table = pq.read_table(io.BytesIO(file_bytes))
+        rows = table.to_pylist()
+        return await self.process_data_columns(rows, path)

packages/graphrag-input/pyproject.toml

@@ -34,7 +34,8 @@ dependencies = [
     "graphrag-storage==3.0.8    ",
     "pydantic~=2.10",
     "markitdown~=0.1.0",
-    "markitdown[pdf]"
+    "markitdown[pdf]",
+    "pyarrow>=14.0.0"
 ]
 
 [project.urls]

tests/unit/indexing/input/test_parquet_loader.py

@@ -0,0 +1,61 @@
+# Copyright (c) 2024 Microsoft Corporation.
+# Licensed under the MIT License
+
+from graphrag_input import InputConfig, InputType, create_input_reader
+from graphrag_storage import StorageConfig, create_storage
+
+
+async def test_parquet_loader_one_file():
+    config = InputConfig(
+        type=InputType.Parquet,
+        file_pattern=".*\\.parquet$",
+    )
+    storage = create_storage(
+        StorageConfig(
+            base_dir="tests/unit/indexing/input/data/one-parquet",
+        )
+    )
+    reader = create_input_reader(config, storage)
+    documents = await reader.read_files()
+    assert len(documents) == 2
+    assert documents[0].title == "input.parquet (0)"
+    assert documents[0].raw_data == {
+        "title": "Hello",
+        "text": "Hi how are you today?",
+    }
+    assert documents[1].title == "input.parquet (1)"
+
+
+async def test_parquet_loader_one_file_with_title():
+    config = InputConfig(
+        type=InputType.Parquet,
+        title_column="title",
+    )
+    storage = create_storage(
+        StorageConfig(
+            base_dir="tests/unit/indexing/input/data/one-parquet",
+        )
+    )
+    reader = create_input_reader(config, storage)
+    documents = await reader.read_files()
+    assert len(documents) == 2
+    assert documents[0].title == "Hello"
+    assert documents[1].title == "World"
+
+
+async def test_parquet_loader_text_content():
+    config = InputConfig(
+        type=InputType.Parquet,
+        text_column="text",
+        title_column="title",
+    )
+    storage = create_storage(
+        StorageConfig(
+            base_dir="tests/unit/indexing/input/data/one-parquet",
+        )
+    )
+    reader = create_input_reader(config, storage)
+    documents = await reader.read_files()
+    assert len(documents) == 2
+    assert documents[0].text == "Hi how are you today?"
+    assert documents[1].text == "This is a test."