perf: optimize time-series write/read hot paths (10's to 100's of ns savings, 2-25x better)

benchmarks/micro/bench_bind_no_encryption.py

@@ -0,0 +1,106 @@
+# Copyright ScyllaDB, Inc.
+#
+# 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.
+
+"""
+Micro-benchmark: BoundStatement.bind() fast path without column encryption.
+
+Measures the improvement from skipping ColDesc namedtuple creation and
+ce_policy checks when column_encryption_policy is None (the common case).
+
+Run:
+    python benchmarks/bench_bind_no_encryption.py
+"""
+
+import datetime
+import sys
+import timeit
+from unittest.mock import MagicMock
+
+from cassandra.query import BoundStatement, PreparedStatement
+from cassandra.cqltypes import (
+    DateType, Int32Type, DoubleType, FloatType, UTF8Type,
+    BooleanType, LongType,
+)
+
+
+def make_prepared_statement(col_names, col_types):
+    """Build a mock PreparedStatement with the given columns."""
+    col_meta = []
+    for name, ctype in zip(col_names, col_types):
+        cm = MagicMock()
+        cm.name = name
+        cm.keyspace_name = 'ks'
+        cm.table_name = 'metrics'
+        cm.type = ctype
+        col_meta.append(cm)
+
+    ps = MagicMock(spec=PreparedStatement)
+    ps.column_metadata = col_meta
+    ps.routing_key_indexes = None
+    ps.protocol_version = 4
+    ps.column_encryption_policy = None
+    ps.serial_consistency_level = None
+    ps.retry_policy = None
+    ps.consistency_level = None
+    ps.fetch_size = None
+    ps.custom_payload = None
+    ps.is_idempotent = False
+    return ps
+
+
+def bench():
+    schemas = [
+        (
+            "3-col (int, double, text)",
+            ['id', 'value', 'tag'],
+            [Int32Type, DoubleType, UTF8Type],
+            [42, 3.14159, 'sensor-001'],
+        ),
+        (
+            "5-col time-series",
+            ['ts', 'sensor_id', 'value', 'quality', 'tag'],
+            [DateType, Int32Type, DoubleType, FloatType, UTF8Type],
+            [datetime.datetime(2025, 4, 5, 12, 0, 0, 123456), 42, 3.14, 0.95, 'alpha'],
+        ),
+        (
+            "8-col wide row",
+            ['ts', 'id', 'v1', 'v2', 'v3', 'v4', 'flag', 'name'],
+            [DateType, LongType, DoubleType, DoubleType, FloatType, FloatType, BooleanType, UTF8Type],
+            [datetime.datetime(2025, 1, 1), 12345678, 1.1, 2.2, 3.3, 4.4, True, 'test-row'],
+        ),
+    ]
+
+    n = 200_000
+    print(f"=== BoundStatement.bind() no-encryption fast path ({n:,} iters) ===\n")
+
+    for label, col_names, col_types, row in schemas:
+        ps = make_prepared_statement(col_names, col_types)
+
+        def do_bind():
+            bs = BoundStatement(ps)
+            bs.bind(row)
+
+        # Warmup
+        for _ in range(1000):
+            do_bind()
+
+        t = timeit.timeit(do_bind, number=n)
+        ns_per = t / n * 1e9
+        print(f"  {label}:")
+        print(f"    {ns_per:.1f} ns/call ({n:,} iters)")
+
+
+if __name__ == "__main__":
+    print(f"Python {sys.version}\n")
+    bench()

benchmarks/micro/bench_cql_parameterized_type.py

@@ -0,0 +1,85 @@
+# Copyright ScyllaDB, Inc.
+#
+# 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.
+
+"""
+Micro-benchmark: cql_parameterized_type memoization.
+
+Measures the cost of building the CQL type string representation
+with and without memoization for various type complexities.
+
+Run:
+    python benchmarks/bench_cql_parameterized_type.py
+"""
+
+import sys
+import timeit
+
+from cassandra.cqltypes import (
+    MapType, SetType, ListType, TupleType,
+    Int32Type, UTF8Type, FloatType, DoubleType, BooleanType,
+)
+
+
+def bench():
+    # Create parameterized types
+    map_type = MapType.apply_parameters([UTF8Type, Int32Type])
+    set_type = SetType.apply_parameters([FloatType])
+    list_type = ListType.apply_parameters([DoubleType])
+    tuple_type = TupleType.apply_parameters([Int32Type, UTF8Type, BooleanType])
+    nested_type = MapType.apply_parameters([
+        UTF8Type,
+        ListType.apply_parameters([
+            TupleType.apply_parameters([Int32Type, FloatType, DoubleType])
+        ])
+    ])
+
+    test_types = [
+        ("Int32Type (simple)", Int32Type),
+        ("MapType<text, int>", map_type),
+        ("SetType<float>", set_type),
+        ("ListType<double>", list_type),
+        ("TupleType<int, text, bool>", tuple_type),
+        ("MapType<text, list<tuple<int, float, double>>>", nested_type),
+    ]
+
+    n = 500_000
+    print(f"=== cql_parameterized_type ({n:,} iters) ===\n")
+
+    for label, typ in test_types:
+        # Clear cache to measure uncached
+        typ._cql_type_str = None
+        # One call to populate cache
+        result = typ.cql_parameterized_type()
+
+        # Measure cached (warm)
+        t_cached = timeit.timeit(typ.cql_parameterized_type, number=n)
+
+        # Measure uncached (cold)
+        def uncached():
+            typ._cql_type_str = None
+            return typ.cql_parameterized_type()
+        t_uncached = timeit.timeit(uncached, number=n)
+
+        saving_ns = (t_uncached - t_cached) / n * 1e9
+        speedup = t_uncached / t_cached if t_cached > 0 else float('inf')
+        print(f"  {label}:")
+        print(f"    result: {result}")
+        print(f"    uncached: {t_uncached / n * 1e9:.1f} ns, "
+              f"cached: {t_cached / n * 1e9:.1f} ns, "
+              f"saving: {saving_ns:.1f} ns ({speedup:.1f}x)")
+
+
+if __name__ == "__main__":
+    print(f"Python {sys.version}\n")
+    bench()