refactor(bigframes): Modularize compiler routing as proxy executor

packages/bigframes/bigframes/session/__init__.py

@@ -80,7 +80,7 @@
 from bigframes import version
 from bigframes.core import blocks, utils
 from bigframes.core.logging import log_adapter
-from bigframes.session import bigquery_session, bq_caching_executor, executor
+from bigframes.session import bigquery_session, executor, proxy_executor
 
 # Avoid circular imports.
 if typing.TYPE_CHECKING:
@@ -316,7 +316,7 @@ def __init__(
         if not self._strictly_ordered:
             labels["bigframes-mode"] = "unordered"
 
-        self._executor: executor.Executor = bq_caching_executor.BigQueryCachingExecutor(
+        self._executor: executor.Executor = proxy_executor.DualCompilerProxyExecutor(
             bqclient=self._clients_provider.bqclient,
             bqstoragereadclient=self._clients_provider.bqstoragereadclient,
             loader=self._loader,

packages/bigframes/bigframes/session/bq_caching_executor.py

@@ -17,15 +17,12 @@
 import concurrent.futures
 import math
 import threading
-import uuid
-import warnings
 from typing import Literal, Mapping, Optional, Sequence, Tuple
 
 import google.api_core.exceptions
 import google.cloud.bigquery.job as bq_job
 import google.cloud.bigquery.table as bq_table
 import google.cloud.bigquery_storage_v1
-import google.cloud.exceptions
 from google.cloud import bigquery
 
 import bigframes
@@ -84,10 +81,14 @@ def __init__(
         enable_polars_execution: bool = False,
         publisher: bigframes.core.events.Publisher,
         labels: Mapping[str, str] = {},
+        compiler_name: Literal["ibis", "sqlglot"] = "ibis",
+        cache: Optional[execution_cache.ExecutionCache] = None,
     ):
         self.bqclient = bqclient
         self.storage_manager = storage_manager
-        self.cache: execution_cache.ExecutionCache = execution_cache.ExecutionCache()
+        self.cache: execution_cache.ExecutionCache = (
+            cache or execution_cache.ExecutionCache()
+        )
         self.metrics = metrics
         self.loader = loader
         self.bqstoragereadclient = bqstoragereadclient
@@ -111,6 +112,7 @@ def __init__(
                 polars_executor.PolarsExecutor(),
             )
         self._upload_lock = threading.Lock()
+        self._compiler_name = compiler_name
 
     def to_sql(
         self,
@@ -127,7 +129,10 @@ def to_sql(
             else array_value.node
         )
         node = self._substitute_large_local_sources(node)
-        compiled = self._compile(node, ordered=ordered)
+        compiled = compile.compile_sql(
+            compile.CompileRequest(node, sort_rows=ordered),
+            compiler_name=self._compiler_name,
+        )
         return compiled.sql
 
     def execute(
@@ -158,7 +163,11 @@ def execute(
                     "Ordering and peeking not supported for gbq export"
                 )
             # separate path for export_gbq, as it has all sorts of annoying logic, such as possibly running as dml
-            result = self._export_gbq(array_value, execution_spec.destination_spec)
+            result = self._export_gbq(
+                array_value,
+                execution_spec.destination_spec,
+                extra_labels=dict(execution_spec.labels),
+            )
             self._publisher.publish(
                 bigframes.core.events.ExecutionFinished(
                     result=result,
@@ -174,6 +183,7 @@ def execute(
             if isinstance(execution_spec.destination_spec, ex_spec.CacheSpec)
             else None,
             must_create_table=not execution_spec.promise_under_10gb,
+            extra_labels=dict(execution_spec.labels),
         )
         # post steps: export
         if isinstance(execution_spec.destination_spec, ex_spec.GcsOutputSpec):
@@ -233,7 +243,10 @@ def _maybe_find_existing_table(
             return None
 
     def _export_gbq(
-        self, array_value: bigframes.core.ArrayValue, spec: ex_spec.TableOutputSpec
+        self,
+        array_value: bigframes.core.ArrayValue,
+        spec: ex_spec.TableOutputSpec,
+        extra_labels: Mapping[str, str] = {},
     ) -> executor.ExecuteResult:
         """
         Export the ArrayValue to an existing BigQuery table.
@@ -243,55 +256,48 @@ def _export_gbq(
         # validate destination table
         existing_table = self._maybe_find_existing_table(spec)
 
-        def run_with_compiler(compiler_name, compiler_id=None):
-            compiled = self._compile(plan, ordered=False, compiler_name=compiler_name)
-            sql = compiled.sql
+        compiled = compile.compile_sql(
+            compile.CompileRequest(plan, sort_rows=False),
+            compiler_name=self._compiler_name,
+        )
+        sql = compiled.sql
 
-            if (existing_table is not None) and _is_schema_match(
-                existing_table.schema, array_value.schema
-            ):
-                # b/409086472: Uses DML for table appends and replacements to avoid
-                # BigQuery `RATE_LIMIT_EXCEEDED` errors, as per quota limits:
-                # https://cloud.google.com/bigquery/quotas#standard_tables
-                job_config = bigquery.QueryJobConfig()
-
-                ir = sqlglot_ir.SQLGlotIR.from_unparsed_query(sql)
-                if spec.if_exists == "append":
-                    sql = sg_sql.to_sql(
-                        sg_sql.insert(ir.expr.as_select_all(), spec.table)
-                    )
-                else:  # for "replace"
-                    assert spec.if_exists == "replace"
-                    sql = sg_sql.to_sql(
-                        sg_sql.replace(ir.expr.as_select_all(), spec.table)
-                    )
-            else:
-                dispositions = {
-                    "fail": bigquery.WriteDisposition.WRITE_EMPTY,
-                    "replace": bigquery.WriteDisposition.WRITE_TRUNCATE,
-                    "append": bigquery.WriteDisposition.WRITE_APPEND,
-                }
-                job_config = bigquery.QueryJobConfig(
-                    write_disposition=dispositions[spec.if_exists],
-                    destination=spec.table,
-                    clustering_fields=spec.cluster_cols if spec.cluster_cols else None,
-                )
+        if (existing_table is not None) and _is_schema_match(
+            existing_table.schema, array_value.schema
+        ):
+            # b/409086472: Uses DML for table appends and replacements to avoid
+            # BigQuery `RATE_LIMIT_EXCEEDED` errors, as per quota limits:
+            # https://cloud.google.com/bigquery/quotas#standard_tables
+            job_config = bigquery.QueryJobConfig()
 
-            # Attach data type usage to the job labels
-            job_config.labels["bigframes-dtypes"] = compiled.encoded_type_refs
-            job_config.labels["bigframes-compiler"] = (
-                f"{compiler_name}-{compiler_id}" if compiler_id else compiler_name
-            )
-            # TODO(swast): plumb through the api_name of the user-facing api that
-            # caused this query.
-            iterator, job = self._run_execute_query(
-                sql=sql,
-                job_config=job_config,
-                session=array_value.session,
+            ir = sqlglot_ir.SQLGlotIR.from_unparsed_query(sql)
+            if spec.if_exists == "append":
+                sql = sg_sql.to_sql(sg_sql.insert(ir.expr.as_select_all(), spec.table))
+            else:  # for "replace"
+                assert spec.if_exists == "replace"
+                sql = sg_sql.to_sql(sg_sql.replace(ir.expr.as_select_all(), spec.table))
+        else:
+            dispositions = {
+                "fail": bigquery.WriteDisposition.WRITE_EMPTY,
+                "replace": bigquery.WriteDisposition.WRITE_TRUNCATE,
+                "append": bigquery.WriteDisposition.WRITE_APPEND,
+            }
+            job_config = bigquery.QueryJobConfig(
+                write_disposition=dispositions[spec.if_exists],
+                destination=spec.table,
+                clustering_fields=spec.cluster_cols if spec.cluster_cols else None,
             )
-            return iterator, job
 
-        iterator, job = self._compile_with_fallback(run_with_compiler)
+        # Attach data type usage to the job labels
+        job_config.labels["bigframes-dtypes"] = compiled.encoded_type_refs
+        # TODO(swast): plumb through the api_name of the user-facing api that
+        # caused this query.
+        iterator, job = self._run_execute_query(
+            sql=sql,
+            job_config=job_config,
+            session=array_value.session,
+            extra_labels=extra_labels,
+        )
 
         has_special_dtype_col = any(
             t in (bigframes.dtypes.TIMEDELTA_DTYPE, bigframes.dtypes.OBJ_REF_DTYPE)
@@ -359,6 +365,7 @@ def _run_execute_query(
         job_config: Optional[bq_job.QueryJobConfig] = None,
         query_with_job: bool = True,
         session=None,
+        extra_labels: Mapping[str, str] = {},
     ) -> Tuple[bq_table.RowIterator, Optional[bigquery.QueryJob]]:
         """
         Starts BigQuery query job and waits for results.
@@ -369,8 +376,9 @@ def _run_execute_query(
                 bigframes.options.compute.maximum_bytes_billed
             )
 
-        if self._labels:
+        if self._labels or extra_labels:
             job_config.labels.update(self._labels)
+            job_config.labels.update(extra_labels)
 
         try:
             # Trick the type checker into thinking we got a literal.
@@ -420,43 +428,6 @@ def _is_trivially_executable(self, array_value: bigframes.core.ArrayValue):
             self.prepare_plan(array_value.node)
         )
 
-    def _compile(
-        self,
-        node: nodes.BigFrameNode,
-        *,
-        ordered: bool = False,
-        peek: Optional[int] = None,
-        materialize_all_order_keys: bool = False,
-        compiler_name: Literal["sqlglot", "ibis"] = "sqlglot",
-    ) -> compile.CompileResult:
-        return compile.compile_sql(
-            compile.CompileRequest(
-                node,
-                sort_rows=ordered,
-                peek_count=peek,
-                materialize_all_order_keys=materialize_all_order_keys,
-            ),
-            compiler_name=compiler_name,
-        )
-
-    def _compile_with_fallback(self, run_fn):
-        compiler_option = bigframes.options.experiments.sql_compiler
-        if compiler_option == "legacy":
-            return run_fn("ibis")
-        elif compiler_option == "experimental":
-            return run_fn("sqlglot")
-        else:  # stable
-            compiler_id = f"{uuid.uuid1().hex[:12]}"
-            try:
-                return run_fn("sqlglot", compiler_id=compiler_id)
-            except google.cloud.exceptions.BadRequest as e:
-                msg = bfe.format_message(
-                    f"Compiler ID {compiler_id}: BadRequest on sqlglot. "
-                    f"Falling back to ibis. Details: {e.message}"
-                )
-                warnings.warn(msg, category=UserWarning)
-                return run_fn("ibis", compiler_id=compiler_id)
-
     def prepare_plan(
         self,
         plan: nodes.BigFrameNode,
@@ -547,8 +518,9 @@ def _cache_most_complex_subtree(self, node: nodes.BigFrameNode) -> bool:
             max_complexity=QUERY_COMPLEXITY_LIMIT,
             cache=self.cache,
             # Heuristic: subtree_compleixty * (copies of subtree)^2
-            heuristic=lambda complexity, count: math.log(complexity)
-            + 2 * math.log(count),
+            heuristic=lambda complexity, count: (
+                math.log(complexity) + 2 * math.log(count)
+            ),
         )
         if selection is None:
             # No good subtrees to cache, just return original tree
@@ -621,6 +593,7 @@ def _execute_plan_gbq(
         peek: Optional[int] = None,
         cache_spec: Optional[ex_spec.CacheSpec] = None,
         must_create_table: bool = True,
+        extra_labels: Mapping[str, str] = {},
     ) -> executor.ExecuteResult:
         """Just execute whatever plan as is, without further caching or decomposition."""
         # TODO(swast): plumb through the api_name of the user-facing api that
@@ -651,43 +624,36 @@ def _execute_plan_gbq(
                 ]
                 cluster_cols = cluster_cols[:_MAX_CLUSTER_COLUMNS]
 
-        def run_with_compiler(compiler_name, compiler_id=None):
-            compiled = self._compile(
+        compiled = compile.compile_sql(
+            compile.CompileRequest(
                 plan,
-                ordered=ordered,
-                peek=peek,
+                sort_rows=ordered,
+                peek_count=peek,
                 materialize_all_order_keys=(cache_spec is not None),
-                compiler_name=compiler_name,
-            )
-            # might have more columns than og schema, for hidden ordering columns
-            compiled_schema = compiled.sql_schema
-
-            destination_table: Optional[bigquery.TableReference] = None
+            ),
+            compiler_name=self._compiler_name,
+        )
+        # might have more columns than og schema, for hidden ordering columns
+        compiled_schema = compiled.sql_schema
 
-            job_config = bigquery.QueryJobConfig()
-            if create_table:
-                destination_table = self.storage_manager.create_temp_table(
-                    compiled_schema, cluster_cols
-                )
-                job_config.destination = destination_table
+        destination_table: Optional[bigquery.TableReference] = None
 
-            # Attach data type usage to the job labels
-            job_config.labels["bigframes-dtypes"] = compiled.encoded_type_refs
-            job_config.labels["bigframes-compiler"] = (
-                f"{compiler_name}-{compiler_id}" if compiler_id else compiler_name
+        job_config = bigquery.QueryJobConfig()
+        if create_table:
+            destination_table = self.storage_manager.create_temp_table(
+                compiled_schema, cluster_cols
             )
-            iterator, query_job = self._run_execute_query(
-                sql=compiled.sql,
-                job_config=job_config,
-                query_with_job=(destination_table is not None),
-                session=plan.session,
-            )
-            return iterator, query_job, compiled
-
-        iterator, query_job, compiled = self._compile_with_fallback(run_with_compiler)
-
-        # might have more columns than og schema, for hidden ordering columns
-        compiled_schema = compiled.sql_schema
+            job_config.destination = destination_table
+
+        # Attach data type usage to the job labels
+        job_config.labels["bigframes-dtypes"] = compiled.encoded_type_refs
+        iterator, query_job = self._run_execute_query(
+            sql=compiled.sql,
+            job_config=job_config,
+            query_with_job=(destination_table is not None),
+            session=plan.session,
+            extra_labels=extra_labels,
+        )
 
         # we could actually cache even when caching is not explicitly requested, but being conservative for now
         result_bq_data = None

packages/bigframes/bigframes/session/execution_spec.py

@@ -15,7 +15,7 @@
 from __future__ import annotations
 
 import dataclasses
-from typing import Literal, Optional, Union
+from typing import Literal, Mapping, Optional, Union
 
 from google.cloud import bigquery
 
@@ -30,6 +30,11 @@ class ExecutionSpec:
     # This is an optimization flag for gbq execution, it doesn't change semantics, but if promise is falsely made, errors may occur
     promise_under_10gb: bool = False
 
+    labels: tuple[tuple[str, str], ...] = ()
+
+    def add_labels(self, labels: Mapping[str, str]) -> ExecutionSpec:
+        return dataclasses.replace(self, labels=self.labels + tuple(labels.items()))
+
 
 # This one is temporary, in future, caching will not be done through immediate execution, but will label nodes
 # that will be cached only when a super-tree is executed