diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 50549920..59ada084 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -25,7 +25,7 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Set up Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
 
@@ -35,6 +35,11 @@ jobs:
     - name: PyTest
       run: make pytest
 
+    # Pylint is not compatible with Apache Beam in Python 3.11:
+    # https://github.com/pylint-dev/pylint/blob/02616372282fd84862636d58071e6f3c62b53559/pyproject.toml#L38
+    - name: Install Pylint separately.
+      run: pip install pylint
+
     - name: PyLint
       run: make pylint
 
@@ -62,7 +67,7 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Set up Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
 
@@ -117,14 +122,14 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Set up Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.10'
 
     - name: Install dependencies except mlcroissant itself
       run: >
         pip install absl-py \
-          datasets \
+          apache-beam \
           etils[epath] \
           GitPython \
           jsonpath_rw \
@@ -152,14 +157,14 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Set up Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.10'
 
     - name: Install dependencies except mlcroissant itself
       run: >
           pip install absl-py \
-            datasets \
+            apache-beam \
             etils[epath] \
             GitPython \
             jsonpath_rw \
@@ -188,7 +193,7 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Set up Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.11'
 
@@ -217,7 +222,7 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Set up Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.11'
 
@@ -240,7 +245,7 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Set up Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.11'
 
@@ -264,7 +269,7 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Set up Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.11'
 
diff --git a/python/mlcroissant/mlcroissant/_src/datasets.py b/python/mlcroissant/mlcroissant/_src/datasets.py
index 2fffcbfd..67516e27 100644
--- a/python/mlcroissant/mlcroissant/_src/datasets.py
+++ b/python/mlcroissant/mlcroissant/_src/datasets.py
@@ -5,6 +5,7 @@
 from collections.abc import Mapping
 import dataclasses
 import re
+import typing
 from typing import Any
 
 from absl import logging
@@ -18,6 +19,7 @@
 from mlcroissant._src.operation_graph.base_operation import Operation
 from mlcroissant._src.operation_graph.base_operation import Operations
 from mlcroissant._src.operation_graph.execute import execute_downloads
+from mlcroissant._src.operation_graph.execute import execute_operations_in_beam
 from mlcroissant._src.operation_graph.execute import execute_operations_in_streaming
 from mlcroissant._src.operation_graph.execute import execute_operations_sequentially
 from mlcroissant._src.operation_graph.operations import FilterFiles
@@ -27,6 +29,9 @@
 from mlcroissant._src.structure_graph.nodes.metadata import Metadata
 from mlcroissant._src.structure_graph.nodes.source import FileProperty
 
+if typing.TYPE_CHECKING:
+    import apache_beam as beam
+
 Filters = Mapping[str, Any]
 
 
@@ -152,8 +157,7 @@ def __iter__(self):
         # that all operations lie on a single straight line, i.e. have an
         # in-degree of 0 or 1. That means that the operation graph is a single line
         # (without external joins for example).
-        can_stream_dataset = all(d == 1 or d == 2 for _, d in operations.degree())
-        if can_stream_dataset:
+        if _is_streamable_dataset(operations):
             yield from execute_operations_in_streaming(
                 record_set=self.record_set,
                 operations=operations,
@@ -163,6 +167,52 @@ def __iter__(self):
                 record_set=self.record_set, operations=operations
             )
 
+    def beam_reader(self, pipeline: beam.Pipeline):
+        """Returns an Apache Beam reader to generate the dataset using e.g. Spark.
+
+        Example of usage:
+
+        ```python
+        import apache_beam as beam
+        from apache_beam.options.pipeline_options import PipelineOptions
+        import mlcroissant as mlc
+
+        dataset = mlc.Dataset(
+            jsonld="https://huggingface.co/api/datasets/ylecun/mnist/croissant",
+        )
+        pipeline_options = PipelineOptions()
+        with beam.Pipeline(options=pipeline_options) as pipeline:
+            _ = dataset.records("mnist").beam_reader(pipeline)
+        ```
+
+        Only streamable datasets can be used with Beam. A streamable dataset is a
+        dataset that can be generated by a linear sequence of operations - without joins
+        for example. This is the case for Hugging Face datasets. If there are branches,
+        we'd need a more complex Beam pipeline.
+
+        The sharding is done on the filtered files. This is currently optimized for
+        Hugging Face datasets, so it raises an error if the dataset is not a Hugging
+        Face dataset.
+
+        Args:
+            A Beam pipeline.
+
+        Returns:
+            A Beam PCollection with all the records.
+
+        Raises:
+            A ValueError if the dataset is not streamable.
+        """
+        operations = self._filter_interesting_operations(self.filters)
+        execute_downloads(operations)
+        if not _is_streamable_dataset(operations):
+            raise ValueError("only streamable datasets can be used with Beam.")
+        return execute_operations_in_beam(
+            pipeline=pipeline,
+            record_set=self.record_set,
+            operations=operations,
+        )
+
     def _filter_interesting_operations(self, filters: Filters | None) -> Operations:
         """Filters connected operations to `ReadFields(self.record_set)`.
 
@@ -307,3 +357,12 @@ def _validate_filters(filters: Filters):
         " to keep all records whose field `data/split` takes the value `train`."
         f" Instead, we got: {filters=}"
     )
+
+
+def _is_streamable_dataset(operations: Operations):
+    """Whether the operations define a streamable datasets.
+
+    A streamable dataset is a dataset that results from executing a linear sequence of
+    operations without branching (for example, no join).
+    """
+    return all(d == 1 or d == 2 for _, d in operations.degree())
diff --git a/python/mlcroissant/mlcroissant/_src/datasets_test.py b/python/mlcroissant/mlcroissant/_src/datasets_test.py
index 71349d87..d76e58fb 100644
--- a/python/mlcroissant/mlcroissant/_src/datasets_test.py
+++ b/python/mlcroissant/mlcroissant/_src/datasets_test.py
@@ -3,6 +3,9 @@
 import json
 from typing import Any
 
+from apache_beam.testing import test_pipeline
+from apache_beam.testing.util import assert_that
+from apache_beam.testing.util import BeamAssertException
 from etils import epath
 import pytest
 
@@ -114,6 +117,46 @@ def load_records_and_test_equality(
     assert len(expected_records) == length
 
 
+def _equal_to_set(expected):
+    """Checks whether 2 beam.PCollections are equal as sets."""
+
+    def matcher_fn(actual):
+        expected_set = set([
+            json.dumps(record_to_python(element)) for element in list(expected)
+        ])
+        actual_set = set([
+            json.dumps(record_to_python(element)) for element in list(actual)
+        ])
+        if expected_set != actual_set:
+            raise BeamAssertException(
+                f"sets are not equal: {expected_set - actual_set}"
+            )
+
+    return matcher_fn
+
+
+def load_records_with_beam_and_test_equality(
+    version: str,
+    dataset_name: str,
+    record_set_name: str,
+):
+    config = (
+        epath.Path(__file__).parent.parent.parent.parent.parent
+        / "datasets"
+        / version
+        / dataset_name
+    )
+    output_file = config.parent / "output" / f"{record_set_name}.jsonl"
+    with output_file.open("rb") as f:
+        lines = f.readlines()
+        expected_records = [json.loads(line) for line in lines]
+    dataset = datasets.Dataset(config)
+
+    with test_pipeline.TestPipeline() as pipeline:
+        result = dataset.records(record_set_name).beam_reader(pipeline=pipeline)
+        assert_that(result, _equal_to_set(expected_records))
+
+
 # IF (NON)-HERMETIC TESTS FAIL, OR A NEW DATASET IS ADDED:
 # You can regenerate .pkl files by launching
 # ```bash
@@ -150,6 +193,17 @@ def test_hermetic_loading(version, dataset_name, record_set_name, num_records):
     load_records_and_test_equality(version, dataset_name, record_set_name, num_records)
 
 
+@parametrize_version()
+@pytest.mark.parametrize(
+    ["dataset_name", "record_set_name"],
+    [
+        ["simple-parquet/metadata.json", "persons"],
+    ],
+)
+def test_beam_hermetic_loading(version, dataset_name, record_set_name):
+    load_records_with_beam_and_test_equality(version, dataset_name, record_set_name)
+
+
 # Hermetic test cases for croissant >=1.0 only.
 @pytest.mark.parametrize(
     ["dataset_name", "record_set_name", "num_records", "filters"],
diff --git a/python/mlcroissant/mlcroissant/_src/operation_graph/execute.py b/python/mlcroissant/mlcroissant/_src/operation_graph/execute.py
index 9d180f93..25bed5e1 100644
--- a/python/mlcroissant/mlcroissant/_src/operation_graph/execute.py
+++ b/python/mlcroissant/mlcroissant/_src/operation_graph/execute.py
@@ -1,6 +1,10 @@
 """Module to execute operations."""
 
+from __future__ import annotations
+
+import collections
 import concurrent.futures
+import typing
 from typing import Any
 
 from absl import logging
@@ -10,10 +14,14 @@
 from mlcroissant._src.core.issues import GenerationError
 from mlcroissant._src.operation_graph.base_operation import Operation
 from mlcroissant._src.operation_graph.base_operation import Operations
+from mlcroissant._src.operation_graph.operations import FilterFiles
 from mlcroissant._src.operation_graph.operations import ReadFields
 from mlcroissant._src.operation_graph.operations.download import Download
 from mlcroissant._src.operation_graph.operations.read import Read
 
+if typing.TYPE_CHECKING:
+    import apache_beam as beam
+
 
 def execute_downloads(operations: Operations):
     """Executes all the downloads in the graph of operations."""
@@ -124,3 +132,29 @@ def read_all_files():
                 "An error occured during the streaming generation of the dataset, more"
                 f" specifically during the operation {operation}"
             ) from e
+
+
+def execute_operations_in_beam(
+    pipeline: beam.Pipeline, record_set: str, operations: Operations
+):
+    """See beam_reader docstring."""
+    import apache_beam as beam
+
+    list_of_operations = _order_relevant_operations(operations, record_set)
+    queue_of_operations = collections.deque(list_of_operations)
+    files = None
+    operation = None
+    while queue_of_operations:
+        operation = queue_of_operations.popleft()
+        files = operation(files)
+        if isinstance(operation, FilterFiles):
+            break
+    pipeline = pipeline | "Shard by files" >> beam.Create(files)
+    while queue_of_operations:
+        operation = queue_of_operations.popleft()
+        if isinstance(operation, ReadFields):
+            beam_operation = beam.ParDo(operation)
+        else:
+            beam_operation = beam.Map(operation)
+        pipeline |= beam_operation
+    return pipeline
diff --git a/python/mlcroissant/mlcroissant/_src/structure_graph/base_node.py b/python/mlcroissant/mlcroissant/_src/structure_graph/base_node.py
index 0bb5a23a..e57f37d7 100644
--- a/python/mlcroissant/mlcroissant/_src/structure_graph/base_node.py
+++ b/python/mlcroissant/mlcroissant/_src/structure_graph/base_node.py
@@ -344,7 +344,9 @@ def __getstate__(self):
         state = {}
         for field in dataclasses.fields(self):
             if field.name == "ctx":
-                state[field.name] = Context()
+                ctx = Context()
+                ctx.graph = self.ctx.graph
+                state[field.name] = ctx
             else:
                 state[field.name] = getattr(self, field.name)
         return state
diff --git a/python/mlcroissant/pyproject.toml b/python/mlcroissant/pyproject.toml
index ef919b38..fd5f8b72 100644
--- a/python/mlcroissant/pyproject.toml
+++ b/python/mlcroissant/pyproject.toml
@@ -42,16 +42,15 @@ documentation = "https://mlcommons.org/working-groups/data/croissant/"
 # Installed through `pip install -e .[dev]`
 dev = [
   "black==23.11.0",
-  "datasets",
   "flake8-docstrings",
   "mlcroissant[audio]",
+  "mlcroissant[beam]",
   "mlcroissant[git]",
   "mlcroissant[image]",
   "mlcroissant[parquet]",
   "mypy",
   "pyflakes",
   "pygraphviz",
-  "pylint",
   "pytest",
   "pytype",
   "torchdata",
@@ -61,6 +60,9 @@ audio = [
   "librosa",
   "soxr==0.4.0b1",
 ]
+beam = [
+  "apache-beam",
+]
 git = ["GitPython"]
 image = ["Pillow"]
 parquet = ["pyarrow"]
@@ -89,7 +91,7 @@ disable_error_code = "attr-defined"
 [[tool.mypy.overrides]]
 module = [
   "absl",
-  "datasets",
+  "apache-beam",
   "etils.*",
   "jsonpath_rw",
   "librosa",