feat: add spanner based aggregation framework

pipeline/workflow/ingestion-helper/aggregation_spec_utils.py

@@ -0,0 +1,165 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import json
+import os
+from dataclasses import dataclass
+from typing import Any, Callable, Dict, Iterable, List, Optional
+
+
+Row = Dict[str, Any]
+Mapper = Callable[[Row], Optional[Row]]
+
+
+@dataclass
+class AggregationSpec:
+    name: str
+    source: Any
+    sink: Any
+    mapper: Optional[Mapper] = None
+
+
+class SpannerSqlSource:
+
+    def __init__(self,
+                 database: Any,
+                 sql: str,
+                 params: Optional[Dict[str, Any]] = None,
+                 param_types: Optional[Dict[str, Any]] = None) -> None:
+        self.database = database
+        self.sql = sql
+        self.params = params or {}
+        self.param_types = param_types or {}
+
+    def read(self) -> Iterable[Row]:
+        with self.database.snapshot() as snapshot:
+            results = snapshot.execute_sql(self.sql,
+                                           params=self.params,
+                                           param_types=self.param_types)
+            field_names = None
+            for row in results:
+                if isinstance(row, dict):
+                    yield row
+                    continue
+
+                if field_names is None:
+                    field_names = [
+                        field.name for field in getattr(results, 'fields', [])
+                    ]
+
+                if field_names:
+                    yield dict(zip(field_names, row))
+                else:
+                    yield {"value": row}
+
+
+class LocalJsonlSource:
+
+    def __init__(self, path: str) -> None:
+        self.path = path
+
+    def read(self) -> Iterable[Row]:
+        with open(self.path, 'r', encoding='utf-8') as jsonl_file:
+            for line in jsonl_file:
+                line = line.strip()
+                if line:
+                    yield json.loads(line)
+
+
+class SpannerTableSink:
+
+    def __init__(self,
+                 database: Any,
+                 table: str,
+                 columns: List[str],
+                 batch_size: int = 1000) -> None:
+        self.database = database
+        self.table = table
+        self.columns = columns
+        self.batch_size = batch_size
+
+    def start(self) -> None:
+        pass
+
+    def write_many(self, rows: List[Row]) -> None:
+        if not rows:
+            return
+
+        values = [[row[column] for column in self.columns] for row in rows]
+        # Use a mutation pool here if this sink needs higher write throughput.
+        with self.database.batch() as batch:
+            batch.insert_or_update(table=self.table,
+                                   columns=self.columns,
+                                   values=values)
+
+    def close(self) -> None:
+        pass
+
+
+class LocalJsonlSink:
+
+    def __init__(self, path: str, batch_size: int = 1000) -> None:
+        self.path = path
+        self.batch_size = batch_size
+        self._file = None
+
+    def start(self) -> None:
+        directory = os.path.dirname(self.path)
+        if directory:
+            os.makedirs(directory, exist_ok=True)
+        self._file = open(self.path, 'w', encoding='utf-8')
+
+    def write_many(self, rows: List[Row]) -> None:
+        if not self._file:
+            raise RuntimeError("LocalJsonlSink must be started before writing")
+        for row in rows:
+            self._file.write(json.dumps(row, sort_keys=True) + '\n')
+
+    def close(self) -> None:
+        if self._file:
+            self._file.close()
+            self._file = None
+
+
+class AggregationRunner:
+
+    def run(self, spec: AggregationSpec) -> int:
+        mapper = spec.mapper or _identity_mapper
+        batch = []
+        row_count = 0
+
+        spec.sink.start()
+        try:
+            for row in spec.source.read():
+                mapped_row = mapper(row)
+                if mapped_row is None:
+                    continue
+
+                batch.append(mapped_row)
+                if len(batch) >= spec.sink.batch_size:
+                    spec.sink.write_many(batch)
+                    row_count += len(batch)
+                    batch = []
+
+            if batch:
+                spec.sink.write_many(batch)
+                row_count += len(batch)
+
+            return row_count
+        finally:
+            spec.sink.close()
+
+
+def _identity_mapper(row: Row) -> Row:
+    return row

pipeline/workflow/ingestion-helper/aggregation_spec_utils_test.py

@@ -0,0 +1,217 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import json
+import tempfile
+import unittest
+from pathlib import Path
+from unittest.mock import MagicMock
+
+from aggregation_spec_utils import AggregationRunner
+from aggregation_spec_utils import AggregationSpec
+from aggregation_spec_utils import LocalJsonlSink
+from aggregation_spec_utils import LocalJsonlSource
+from aggregation_spec_utils import SpannerSqlSource
+from aggregation_spec_utils import SpannerTableSink
+
+
+class MockField:
+
+    def __init__(self, name):
+        self.name = name
+
+
+class MockResults:
+
+    def __init__(self, rows, field_names):
+        self.rows = rows
+        self.fields = [MockField(name) for name in field_names]
+
+    def __iter__(self):
+        return iter(self.rows)
+
+
+class DelayedFieldResults:
+
+    def __init__(self, rows, field_names):
+        self.rows = rows
+        self.field_names = field_names
+        self._iteration_started = False
+
+    @property
+    def fields(self):
+        if not self._iteration_started:
+            return []
+        return [MockField(name) for name in self.field_names]
+
+    def __iter__(self):
+        self._iteration_started = True
+        return iter(self.rows)
+
+
+class TestAggregationSpecUtils(unittest.TestCase):
+
+    def test_local_jsonl_source_to_local_jsonl_sink(self):
+        with tempfile.TemporaryDirectory() as temp_dir:
+            input_path = Path(temp_dir) / 'input.jsonl'
+            output_path = Path(temp_dir) / 'output.jsonl'
+            self._write_jsonl(input_path, [{
+                'subject_id': 'dc/1'
+            }, {
+                'subject_id': 'dc/2'
+            }])
+
+            count = AggregationRunner().run(
+                AggregationSpec(
+                    name='copy',
+                    source=LocalJsonlSource(str(input_path)),
+                    sink=LocalJsonlSink(str(output_path), batch_size=1),
+                ))
+
+            self.assertEqual(count, 2)
+            self.assertEqual(self._read_jsonl(output_path), [{
+                'subject_id': 'dc/1'
+            }, {
+                'subject_id': 'dc/2'
+            }])
+
+    def test_mapper_transforms_row_shape(self):
+        with tempfile.TemporaryDirectory() as temp_dir:
+            input_path = Path(temp_dir) / 'input.jsonl'
+            output_path = Path(temp_dir) / 'output.jsonl'
+            self._write_jsonl(input_path, [{'source': 'dc/1'}])
+
+            count = AggregationRunner().run(
+                AggregationSpec(
+                    name='mapped',
+                    source=LocalJsonlSource(str(input_path)),
+                    sink=LocalJsonlSink(str(output_path)),
+                    mapper=lambda row: {'subject_id': row['source']},
+                ))
+
+            self.assertEqual(count, 1)
+            self.assertEqual(self._read_jsonl(output_path),
+                             [{'subject_id': 'dc/1'}])
+
+    def test_spanner_source_streams_named_rows_from_snapshot(self):
+        database = MagicMock()
+        snapshot = database.snapshot.return_value.__enter__.return_value
+        snapshot.execute_sql.return_value = MockResults(
+            rows=[('dc/1', 'Node 1'), ('dc/2', 'Node 2')],
+            field_names=['subject_id', 'name'],
+        )
+        source = SpannerSqlSource(database,
+                                  'SELECT subject_id, name FROM Node',
+                                  params={'limit': 2},
+                                  param_types={'limit': 'INT64'})
+
+        rows = list(source.read())
+
+        self.assertEqual(rows, [{
+            'subject_id': 'dc/1',
+            'name': 'Node 1'
+        }, {
+            'subject_id': 'dc/2',
+            'name': 'Node 2'
+        }])
+        snapshot.execute_sql.assert_called_once_with(
+            'SELECT subject_id, name FROM Node',
+            params={'limit': 2},
+            param_types={'limit': 'INT64'},
+        )
+
+    def test_spanner_source_reads_fields_after_stream_starts(self):
+        database = MagicMock()
+        snapshot = database.snapshot.return_value.__enter__.return_value
+        snapshot.execute_sql.return_value = DelayedFieldResults(
+            rows=[('dc/1', 'Node 1')],
+            field_names=['subject_id', 'name'],
+        )
+
+        rows = list(
+            SpannerSqlSource(database,
+                             'SELECT subject_id, name FROM Node').read())
+
+        self.assertEqual(rows, [{'subject_id': 'dc/1', 'name': 'Node 1'}])
+
+    def test_spanner_sink_writes_multiple_batches(self):
+        with tempfile.TemporaryDirectory() as temp_dir:
+            input_path = Path(temp_dir) / 'input.jsonl'
+            self._write_jsonl(input_path, [{
+                'subject_id': f'dc/{idx}'
+            } for idx in range(5)])
+
+            database = MagicMock()
+            batches = []
+
+            def make_batch_context():
+                context = MagicMock()
+                batch = MagicMock()
+                context.__enter__.return_value = batch
+                batches.append(batch)
+                return context
+
+            database.batch.side_effect = make_batch_context
+            sink = SpannerTableSink(database,
+                                    table='Node',
+                                    columns=['subject_id'],
+                                    batch_size=2)
+
+            count = AggregationRunner().run(
+                AggregationSpec(
+                    name='write_nodes',
+                    source=LocalJsonlSource(str(input_path)),
+                    sink=sink,
+                ))
+
+            self.assertEqual(count, 5)
+            self.assertEqual(database.batch.call_count, 3)
+            self.assertEqual(
+                [call.kwargs['values'] for batch in batches
+                 for call in batch.insert_or_update.call_args_list],
+                [[['dc/0'], ['dc/1']], [['dc/2'], ['dc/3']], [['dc/4']]],
+            )
+
+    def test_empty_source_writes_nothing(self):
+        with tempfile.TemporaryDirectory() as temp_dir:
+            input_path = Path(temp_dir) / 'input.jsonl'
+            input_path.write_text('', encoding='utf-8')
+            database = MagicMock()
+
+            count = AggregationRunner().run(
+                AggregationSpec(
+                    name='empty',
+                    source=LocalJsonlSource(str(input_path)),
+                    sink=SpannerTableSink(database,
+                                          table='Node',
+                                          columns=['subject_id'],
+                                          batch_size=2),
+                ))
+
+            self.assertEqual(count, 0)
+            database.batch.assert_not_called()
+
+    def _write_jsonl(self, path, rows):
+        path.write_text(''.join(json.dumps(row) + '\n' for row in rows),
+                        encoding='utf-8')
+
+    def _read_jsonl(self, path):
+        return [
+            json.loads(line)
+            for line in path.read_text(encoding='utf-8').splitlines()
+        ]
+
+
+if __name__ == '__main__':
+    unittest.main()