57 lines
1.9 KiB
Python
57 lines
1.9 KiB
Python
# Copyright 2023 Memgraph Ltd.
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#
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# Use of this software is governed by the Business Source License
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# included in the file licenses/BSL.txt; by using this file, you agree to be bound by the terms of the Business Source
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# License, and you may not use this file except in compliance with the Business Source License.
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#
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# As of the Change Date specified in that file, in accordance with
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# the Business Source License, use of this software will be governed
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# by the Apache License, Version 2.0, included in the file
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# licenses/APL.txt.
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import random
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from workloads.base import Workload
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class Demo(Workload):
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NAME = "demo"
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def indexes_generator(self):
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indexes = []
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if "neo4j" in self.benchmark_context.vendor_name:
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indexes.extend(
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[
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("CREATE INDEX FOR (n:NodeA) ON (n.id);", {}),
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("CREATE INDEX FOR (n:NodeB) ON (n.id);", {}),
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]
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)
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else:
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indexes.extend(
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[
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("CREATE INDEX ON :NodeA(id);", {}),
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("CREATE INDEX ON :NodeB(id);", {}),
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]
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)
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return indexes
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def dataset_generator(self):
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queries = []
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for i in range(0, 10000):
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queries.append(("CREATE (:NodeA {id: $id});", {"id": i}))
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queries.append(("CREATE (:NodeB {id: $id});", {"id": i}))
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for i in range(0, 50000):
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a = random.randint(0, 9999)
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b = random.randint(0, 9999)
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queries.append(
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(("MATCH(a:NodeA {id: $A_id}),(b:NodeB{id: $B_id}) CREATE (a)-[:EDGE]->(b)"), {"A_id": a, "B_id": b})
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)
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return queries
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def benchmark__test__get_nodes(self):
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return ("MATCH (n) RETURN n;", {})
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def benchmark__test__get_node_by_id(self):
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return ("MATCH (n:NodeA{id: $id}) RETURN n;", {"id": random.randint(0, 9999)})
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