Add script for running TPC-H

tpch/README.md

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+<!---
+  Licensed to the Apache Software Foundation (ASF) under one
+  or more contributor license agreements.  See the NOTICE file
+  distributed with this work for additional information
+  regarding copyright ownership.  The ASF licenses this file
+  to you 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.
+-->
+
+# TPC-H
+
+## Running Benchmarks
+
+```shell
+ RAY_ADDRESS='http://10.0.0.23:8265'  ray job submit --working-dir `pwd` -- python3 tpcbench.py --benchmark tpch --data /path/to/data --queries /path/to/tpch/queries --concurrency 16
+```

tpch/tpcbench.py

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+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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 argparse
+import ray
+from datafusion_ray import DatafusionRayContext
+from datetime import datetime
+import json
+import time
+
+def main(benchmark: str, data_path: str, query_path: str, concurrency: int):
+
+    # Register the tables
+    if benchmark == "tpch":
+        num_queries = 22
+        table_names = ["customer", "lineitem", "nation", "orders", "part", "partsupp", "region", "supplier"]
+    elif benchmark == "tpcds":
+        num_queries = 99
+        table_names = ["call_center", "catalog_page", "catalog_returns", "catalog_sales", "customer",
+           "customer_address", "customer_demographics", "date_dim", "time_dim", "household_demographics",
+           "income_band", "inventory", "item", "promotion", "reason", "ship_mode", "store", "store_returns",
+           "store_sales", "warehouse", "web_page", "web_returns", "web_sales", "web_site"]
+    else:
+        raise "invalid benchmark"
+
+    # Connect to a cluster
+    # use ray job submit
+    ray.init()
+
+    ctx = DatafusionRayContext(concurrency)
+
+    for table in table_names:
+        path = f"{data_path}/{table}.parquet"
+        print(f"Registering table {table} using path {path}")
+        ctx.register_parquet(table, path)
+
+    results = {
+        'engine': 'datafusion-python',
+        'benchmark': benchmark,
+        'data_path': data_path,
+        'query_path': query_path,
+        'concurrency': concurrency,
+    }
+
+    for query in range(1, num_queries + 1):
+        # read text file
+        path = f"{query_path}/q{query}.sql"
+        print(f"Reading query {query} using path {path}")
+        with open(path, "r") as f:
+            text = f.read()
+            # each file can contain multiple queries
+            queries = text.split(";")
+
+            start_time = time.time()
+            for sql in queries:
+                sql = sql.strip()
+                if len(sql) > 0:
+                    print(f"Executing: {sql}")
+                    df = ctx.sql(sql)
+                    rows = df.collect()
+
+                    print(f"Query {query} returned {len(rows)} rows")
+            end_time = time.time()
+            print(f"Query {query} took {end_time - start_time} seconds")
+
+            # store timings in list and later add option to run > 1 iterations
+            results[query] = [end_time - start_time]
+
+    str = json.dumps(results, indent=4)
+    current_time_millis = int(datetime.now().timestamp() * 1000)
+    results_path = f"datafusion-python-{benchmark}-{current_time_millis}.json"
+    print(f"Writing results to {results_path}")
+    with open(results_path, "w") as f:
+        f.write(str)
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="DataFusion benchmark derived from TPC-H / TPC-DS")
+    parser.add_argument("--benchmark", required=True, help="Benchmark to run (tpch or tpcds)")
+    parser.add_argument("--data", required=True, help="Path to data files")
+    parser.add_argument("--queries", required=True, help="Path to query files")
+    parser.add_argument("--concurrency", required=True, help="Number of concurrent tasks")
+    args = parser.parse_args()
+
+    main(args.benchmark, args.data, args.queries, int(args.concurrency))