szehon-ho commented on code in PR #56069:
URL: https://github.com/apache/spark/pull/56069#discussion_r3293756267
##########
python/pyspark/pipelines/api.py:
##########
@@ -525,3 +527,190 @@ def create_sink(
comment=None,
)
get_active_graph_element_registry().register_output(sink)
+
+
+def create_auto_cdc_flow(
+ target: str,
+ source: str,
+ keys: Union[List[str], List[Column]],
+ sequence_by: Union[str, Column],
+ apply_as_deletes: Optional[Union[str, Column]] = None,
+ column_list: Optional[Union[List[str], List[Column]]] = None,
+ except_column_list: Optional[Union[List[str], List[Column]]] = None,
+ stored_as_scd_type: Optional[Literal[1, "1"]] = None,
+ name: Optional[str] = None,
+) -> None:
+ """
+ Create an Auto CDC flow into the target table from the Change Data Capture
(CDC) source.
+ Target table must have already been created using create_streaming_table
function. Only one
+ of column_list and except_column_list can be specified.
+
+ Example:
+ create_auto_cdc_flow(
+ target="target",
+ source="source",
+ keys=["key"],
+ sequence_by="sequence_expr",
+ column_list=["key", "value"],
+ )
+
+ Note that for keys, sequence_by, column_list, and except_column_list the
arguments have to
+ be column identifiers without qualifiers, e.g. they cannot be
col("sourceTable.keyId").
+
+ :param target: The name of the target table that receives the Auto CDC
flow.
+ :param source: The name of the CDC source to stream from.
+ :param keys: The column or combination of columns that uniquely identify a
row in the source \
+ data. This is used to identify which CDC events apply to specific
records in the target \
+ table. These keys also identify records in the target table, e.g., if
there exists a record \
+ for given keys and the CDC source has an UPSERT operation for the same
keys, we will update \
+ the existing record. At least one key must be provided. This should be
a list of column \
+ identifiers without qualifiers, expressed as either Python strings or
PySpark Columns.
+ :param sequence_by: An expression that we use to order the source data.
This can be expressed \
+ as either a SQL expression string or a PySpark Column.
+ :param apply_as_deletes: Delete condition for the merged operation. This
should be a string of \
+ expression e.g. "operation = 'DELETE'"
+ :param column_list: Columns that will be included in the output table.
This should be a list \
+ of column identifiers without qualifiers, expressed as either Python
strings or PySpark \
+ Column. Only one of column_list and except_column_list can be
specified.
+ :param except_column_list: Columns that will be excluded in the output
table. This should be a \
+ list of column identifiers without qualifiers, expressed as either
Python strings or \
+ PySpark Column. Only one of column_list and except_column_list can be
specified. When this \
+ is specified, all columns in the dataframe of the target table except
those in this list \
+ will be in the output table.
+ :param stored_as_scd_type: The SCD type for the target table. Only 1 (or
"1") is supported. \
+ When not specified the server default applies.
+ :param name: The name of the flow for this create_auto_cdc_flow command.
When unspecified this \
+ will build a "default flow" with name equal to the target name.
+ """
+ if type(target) is not str:
+ raise PySparkTypeError(
+ errorClass="NOT_EXPECTED_TYPE",
+ messageParameters={
+ "arg_name": "target",
+ "expected_type": "str",
+ "arg_type": type(target).__name__,
+ },
+ )
+ if type(source) is not str:
+ raise PySparkTypeError(
+ errorClass="NOT_EXPECTED_TYPE",
+ messageParameters={
+ "arg_name": "source",
+ "expected_type": "str",
+ "arg_type": type(source).__name__,
+ },
+ )
+ if name is not None and type(name) is not str:
+ raise PySparkTypeError(
+ errorClass="NOT_EXPECTED_TYPE",
+ messageParameters={
+ "arg_name": "name",
+ "expected_type": "str",
+ "arg_type": type(name).__name__,
+ },
+ )
+
Review Comment:
Several blank lines here have trailing whitespace (e.g. after the `name`
type check and inside `_normalize_column_list`). Worth stripping — Black/ruff
may flag these on CI.
##########
python/pyspark/pipelines/tests/test_graph_element_registry.py:
##########
@@ -97,6 +100,146 @@ def flow2():
self.assertEqual(sink_obj.options["key1"], "value1")
assert
sink_obj.source_code_location.filename.endswith("test_graph_element_registry.py")
+ def test_create_auto_cdc_flow(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("target")
+ dp.create_auto_cdc_flow(
+ target="target",
+ source="source",
+ keys=[col("key")],
+ sequence_by=expr("seq"),
+ )
+
+ self.assertEqual(len(registry.outputs), 1)
+ self.assertEqual(len(registry.auto_cdc_flows), 1)
+
+ flow = cast(AutoCdcFlow, registry.auto_cdc_flows[0])
+ self.assertEqual(flow.target, "target")
+ self.assertEqual(flow.source, "source")
+
+ # When name is not specified, it inherit's the target's name at
construction time.
+ self.assertEqual(flow.name, "target")
+ self.assertIsNone(flow.stored_as_scd_type)
+ self.assertIsNone(flow.apply_as_deletes)
+ assert
flow.source_code_location.filename.endswith("test_graph_element_registry.py")
+
+ def test_create_auto_cdc_flow_with_all_args(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("tgt")
+ dp.create_auto_cdc_flow(
+ target="tgt",
+ source="src",
+ keys=[col("id")],
+ sequence_by=expr("ts"),
+ apply_as_deletes=expr("op = 'DELETE'"),
+ column_list=[col("id"), col("val")],
+ stored_as_scd_type=1,
+ name="my_flow",
+ )
+
+ flow = cast(AutoCdcFlow, registry.auto_cdc_flows[0])
+ self.assertEqual(flow.name, "my_flow")
+ self.assertEqual(flow.stored_as_scd_type, 1)
+
+ def test_create_auto_cdc_flow_with_string_args(self):
+ # Verify that string forms of column / expression arguments are
normalized to
+ # PySpark Columns, equivalent to passing col(...) / expr(...) directly.
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("tgt")
+ dp.create_auto_cdc_flow(
+ target="tgt",
+ source="src",
+ keys=["id"],
+ sequence_by="ts",
+ apply_as_deletes="op = 'DELETE'",
+ column_list=["id", "val"],
+ )
+
+ flow = cast(AutoCdcFlow, registry.auto_cdc_flows[0])
+ for k in flow.keys:
+ self.assertIsInstance(k, Column)
+ self.assertIsInstance(flow.sequence_by, Column)
+ self.assertIsInstance(flow.apply_as_deletes, Column)
+ assert flow.column_list is not None
+ for c in flow.column_list:
+ self.assertIsInstance(c, Column)
+
+ def test_create_auto_cdc_flow_stored_as_scd_type_string(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("t")
+ dp.create_auto_cdc_flow(
+ target="t",
+ source="s",
+ keys=[col("k")],
+ sequence_by=expr("seq"),
+ stored_as_scd_type="1",
+ )
+
+ flow = cast(AutoCdcFlow, registry.auto_cdc_flows[0])
+ self.assertEqual(flow.stored_as_scd_type, "1")
+
+ def test_create_auto_cdc_flow_invalid_scd_type(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("t")
+ with self.assertRaises(PySparkTypeError) as ctx:
+ dp.create_auto_cdc_flow(
+ target="t",
+ source="s",
+ keys=[col("k")],
+ sequence_by=expr("seq"),
+ stored_as_scd_type=2, # type: ignore[arg-type]
+ )
+ self.assertEqual(ctx.exception.getCondition(), "NOT_EXPECTED_TYPE")
+
+ def test_create_auto_cdc_flow_with_except_column_list(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("tgt")
+ dp.create_auto_cdc_flow(
+ target="tgt",
+ source="src",
+ keys=[col("id")],
+ sequence_by=expr("ts"),
+ except_column_list=["op", "ts"],
+ )
+
+ flow = cast(AutoCdcFlow, registry.auto_cdc_flows[0])
+ self.assertIsNone(flow.column_list)
+ assert flow.except_column_list is not None
+ self.assertEqual(len(flow.except_column_list), 2)
+ for c in flow.except_column_list:
+ self.assertIsInstance(c, Column)
+
+ def test_create_auto_cdc_flow_rejects_non_str_target(self):
Review Comment:
The other `create_auto_cdc_flow` tests call `create_streaming_table` on the
target first. Harmless for `LocalGraphElementRegistry`, but adding it here
would match the doc requirement and keep the tests consistent.
##########
python/pyspark/pipelines/api.py:
##########
@@ -525,3 +527,190 @@ def create_sink(
comment=None,
)
get_active_graph_element_registry().register_output(sink)
+
+
+def create_auto_cdc_flow(
+ target: str,
+ source: str,
+ keys: Union[List[str], List[Column]],
+ sequence_by: Union[str, Column],
+ apply_as_deletes: Optional[Union[str, Column]] = None,
+ column_list: Optional[Union[List[str], List[Column]]] = None,
+ except_column_list: Optional[Union[List[str], List[Column]]] = None,
+ stored_as_scd_type: Optional[Literal[1, "1"]] = None,
+ name: Optional[str] = None,
+) -> None:
+ """
+ Create an Auto CDC flow into the target table from the Change Data Capture
(CDC) source.
+ Target table must have already been created using create_streaming_table
function. Only one
+ of column_list and except_column_list can be specified.
+
+ Example:
+ create_auto_cdc_flow(
Review Comment:
The example uses 2-space continuation indent for arguments; other SDP doc
examples (e.g. `create_streaming_table`) use 4 spaces inside the docstring
block. Worth aligning for consistency:
```python
Example:
create_auto_cdc_flow(
target="target",
source="source",
keys=["key"],
sequence_by="sequence_expr",
column_list=["key", "value"],
)
```
##########
python/pyspark/pipelines/tests/test_graph_element_registry.py:
##########
@@ -97,6 +100,146 @@ def flow2():
self.assertEqual(sink_obj.options["key1"], "value1")
assert
sink_obj.source_code_location.filename.endswith("test_graph_element_registry.py")
+ def test_create_auto_cdc_flow(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("target")
+ dp.create_auto_cdc_flow(
+ target="target",
+ source="source",
+ keys=[col("key")],
+ sequence_by=expr("seq"),
+ )
+
+ self.assertEqual(len(registry.outputs), 1)
+ self.assertEqual(len(registry.auto_cdc_flows), 1)
+
+ flow = cast(AutoCdcFlow, registry.auto_cdc_flows[0])
+ self.assertEqual(flow.target, "target")
+ self.assertEqual(flow.source, "source")
+
+ # When name is not specified, it inherit's the target's name at
construction time.
+ self.assertEqual(flow.name, "target")
+ self.assertIsNone(flow.stored_as_scd_type)
+ self.assertIsNone(flow.apply_as_deletes)
+ assert
flow.source_code_location.filename.endswith("test_graph_element_registry.py")
+
+ def test_create_auto_cdc_flow_with_all_args(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("tgt")
+ dp.create_auto_cdc_flow(
+ target="tgt",
+ source="src",
+ keys=[col("id")],
+ sequence_by=expr("ts"),
+ apply_as_deletes=expr("op = 'DELETE'"),
+ column_list=[col("id"), col("val")],
+ stored_as_scd_type=1,
+ name="my_flow",
+ )
+
+ flow = cast(AutoCdcFlow, registry.auto_cdc_flows[0])
+ self.assertEqual(flow.name, "my_flow")
+ self.assertEqual(flow.stored_as_scd_type, 1)
+
+ def test_create_auto_cdc_flow_with_string_args(self):
+ # Verify that string forms of column / expression arguments are
normalized to
+ # PySpark Columns, equivalent to passing col(...) / expr(...) directly.
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("tgt")
+ dp.create_auto_cdc_flow(
+ target="tgt",
+ source="src",
+ keys=["id"],
+ sequence_by="ts",
+ apply_as_deletes="op = 'DELETE'",
+ column_list=["id", "val"],
+ )
+
+ flow = cast(AutoCdcFlow, registry.auto_cdc_flows[0])
+ for k in flow.keys:
+ self.assertIsInstance(k, Column)
+ self.assertIsInstance(flow.sequence_by, Column)
+ self.assertIsInstance(flow.apply_as_deletes, Column)
+ assert flow.column_list is not None
+ for c in flow.column_list:
+ self.assertIsInstance(c, Column)
+
+ def test_create_auto_cdc_flow_stored_as_scd_type_string(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("t")
+ dp.create_auto_cdc_flow(
+ target="t",
+ source="s",
+ keys=[col("k")],
+ sequence_by=expr("seq"),
+ stored_as_scd_type="1",
+ )
+
+ flow = cast(AutoCdcFlow, registry.auto_cdc_flows[0])
+ self.assertEqual(flow.stored_as_scd_type, "1")
+
+ def test_create_auto_cdc_flow_invalid_scd_type(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("t")
+ with self.assertRaises(PySparkTypeError) as ctx:
+ dp.create_auto_cdc_flow(
+ target="t",
+ source="s",
+ keys=[col("k")],
+ sequence_by=expr("seq"),
+ stored_as_scd_type=2, # type: ignore[arg-type]
+ )
+ self.assertEqual(ctx.exception.getCondition(), "NOT_EXPECTED_TYPE")
+
+ def test_create_auto_cdc_flow_with_except_column_list(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("tgt")
+ dp.create_auto_cdc_flow(
+ target="tgt",
+ source="src",
+ keys=[col("id")],
+ sequence_by=expr("ts"),
+ except_column_list=["op", "ts"],
+ )
+
+ flow = cast(AutoCdcFlow, registry.auto_cdc_flows[0])
+ self.assertIsNone(flow.column_list)
+ assert flow.except_column_list is not None
+ self.assertEqual(len(flow.except_column_list), 2)
+ for c in flow.except_column_list:
+ self.assertIsInstance(c, Column)
+
+ def test_create_auto_cdc_flow_rejects_non_str_target(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ with self.assertRaises(PySparkTypeError) as ctx:
+ dp.create_auto_cdc_flow(
+ target=123, # type: ignore[arg-type]
+ source="src",
+ keys=[col("id")],
+ sequence_by=expr("ts"),
+ )
+ self.assertEqual(ctx.exception.getCondition(), "NOT_EXPECTED_TYPE")
+
+ def test_create_auto_cdc_flow_rejects_invalid_key_element(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("tgt")
+ with self.assertRaises(PySparkTypeError) as ctx:
+ dp.create_auto_cdc_flow(
+ target="tgt",
+ source="src",
+ keys=[123], # type: ignore[list-item]
+ sequence_by=expr("ts"),
+ )
+ self.assertEqual(ctx.exception.getCondition(), "NOT_EXPECTED_TYPE")
+
def test_definition_without_graph_element_registry(self):
Review Comment:
`test_definition_without_graph_element_registry` covers decorators,
`create_streaming_table`, and `append_flow`, but not `create_auto_cdc_flow`.
Could you add a case like:
```python
with self.assertRaises(PySparkException) as context:
dp.create_auto_cdc_flow(
target="t",
source="s",
keys=["k"],
sequence_by="seq",
)
self.assertEqual(
context.exception.getCondition(),
"GRAPH_ELEMENT_DEFINED_OUTSIDE_OF_DECLARATIVE_PIPELINE",
)
```
##########
python/pyspark/pipelines/tests/test_graph_element_registry.py:
##########
@@ -97,6 +100,146 @@ def flow2():
self.assertEqual(sink_obj.options["key1"], "value1")
assert
sink_obj.source_code_location.filename.endswith("test_graph_element_registry.py")
+ def test_create_auto_cdc_flow(self):
+ registry = LocalGraphElementRegistry()
+ with graph_element_registration_context(registry):
+ dp.create_streaming_table("target")
+ dp.create_auto_cdc_flow(
+ target="target",
+ source="source",
+ keys=[col("key")],
+ sequence_by=expr("seq"),
+ )
+
+ self.assertEqual(len(registry.outputs), 1)
+ self.assertEqual(len(registry.auto_cdc_flows), 1)
+
+ flow = cast(AutoCdcFlow, registry.auto_cdc_flows[0])
+ self.assertEqual(flow.target, "target")
+ self.assertEqual(flow.source, "source")
+
+ # When name is not specified, it inherit's the target's name at
construction time.
Review Comment:
Nit: `inherit's` → `inherits`.
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