mattmartin14 commented on code in PR #1534: URL: https://github.com/apache/iceberg-python/pull/1534#discussion_r1941313578
########## tests/table/test_merge_rows.py: ########## @@ -0,0 +1,397 @@ +# 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. + +from pyiceberg.catalog.sql import SqlCatalog +import os +import shutil + +_TEST_NAMESPACE = "test_ns" + +try: + from datafusion import SessionContext +except ModuleNotFoundError as e: + raise ModuleNotFoundError("For merge_rows, DataFusion needs to be installed") from e + +def get_test_warehouse_path(): + curr_dir = os.path.dirname(os.path.abspath(__file__)) + return f"{curr_dir}/warehouse" + +def get_sql_catalog(namespace: str) -> SqlCatalog: + warehouse_path = get_test_warehouse_path() + catalog = SqlCatalog( + "default", + **{ + "uri": f"sqlite:///:memory:", + "warehouse": f"file://{warehouse_path}", + }, + ) + + catalog.create_namespace(namespace=namespace) + return catalog + +def purge_warehouse(): + warehouse_path = get_test_warehouse_path() + + if os.path.exists(warehouse_path): + shutil.rmtree(warehouse_path) + +def show_iceberg_table(table, ctx: SessionContext): + import pyarrow.dataset as ds + table_name = "target" + if ctx.table_exist(table_name): + ctx.deregister_table(table_name) + ctx.register_dataset(table_name, ds.dataset(table.scan().to_arrow())) + ctx.sql(f"SELECT * FROM {table_name} limit 5").show() + +def show_df(df, ctx: SessionContext): + import pyarrow.dataset as ds + ctx.register_dataset("df", ds.dataset(df)) + ctx.sql("select * from df limit 10").show() + +def gen_source_dataset(start_row: int, end_row: int, composite_key: bool, add_dup: bool, ctx: SessionContext): + + additional_columns = ", t.order_id + 1000 as order_line_id" if composite_key else "" + + dup_row = f""" + UNION ALL + ( + SELECT t.order_id {additional_columns} + , date '2021-01-01' as order_date, 'B' as order_type + from t + limit 1 + ) + """ if add_dup else "" + + + sql = f""" + with t as (SELECT unnest(range({start_row},{end_row+1})) as order_id) + SELECT t.order_id {additional_columns} + , date '2021-01-01' as order_date, 'B' as order_type + from t + {dup_row} + """ + + #print(sql) + + df = ctx.sql(sql).to_arrow_table() + + + return df + +def gen_target_iceberg_table(start_row: int, end_row: int, composite_key: bool, ctx: SessionContext): + + additional_columns = ", t.order_id + 1000 as order_line_id" if composite_key else "" + + df = ctx.sql(f""" + with t as (SELECT unnest(range({start_row},{end_row+1})) as order_id) + SELECT t.order_id {additional_columns} + , date '2021-01-01' as order_date, 'A' as order_type + from t + """).to_arrow_table() + + catalog = get_sql_catalog(_TEST_NAMESPACE) + table = catalog.create_table(f"{_TEST_NAMESPACE}.target", df.schema) + + table.append(df) + + return table + +def test_merge_scenario_1a_simple(): + + """ + tests a single insert and update + """ + + ctx = SessionContext() + + table = gen_target_iceberg_table(1, 2, False, ctx) + source_df = gen_source_dataset(2, 3, False, False, ctx) + + res = table.merge_rows(df=source_df, join_cols=["order_id"]) + + rows_updated_should_be = 1 + rows_inserted_should_be = 1 + + assert res['rows_updated'] == rows_updated_should_be, f"rows updated should be {rows_updated_should_be}, but got {res['rows_updated']}" + assert res['rows_inserted'] == rows_inserted_should_be, f"rows inserted should be {rows_inserted_should_be}, but got {res['rows_inserted']}" + + purge_warehouse() + print('merge rows: test scenario 1a pass') + +def test_merge_scenario_1b_simple(): + + """ + tests a single insert and update; skips a row that does not need to be updated + """ + + ctx = SessionContext() + + df = ctx.sql(f""" + select 1 as order_id, date '2021-01-01' as order_date, 'A' as order_type + union all + select 2 as order_id, date '2021-01-01' as order_date, 'A' as order_type + """).to_arrow_table() + + catalog = get_sql_catalog(_TEST_NAMESPACE) + table = catalog.create_table(f"{_TEST_NAMESPACE}.target", df.schema) + + table.append(df) + + source_df = ctx.sql(f""" + select 1 as order_id, date '2021-01-01' as order_date, 'A' as order_type + union all + select 2 as order_id, date '2021-01-01' as order_date, 'B' as order_type + union all + select 3 as order_id, date '2021-01-01' as order_date, 'A' as order_type + """).to_arrow_table() + + res = table.merge_rows(df=source_df, join_cols=["order_id"]) + + rows_updated_should_be = 1 + rows_inserted_should_be = 1 + + assert res['rows_updated'] == rows_updated_should_be, f"rows updated should be {rows_updated_should_be}, but got {res['rows_updated']}" + assert res['rows_inserted'] == rows_inserted_should_be, f"rows inserted should be {rows_inserted_should_be}, but got {res['rows_inserted']}" + + purge_warehouse() + print('merge rows: test scenario 1b (skip 1 row) pass') + + +def test_merge_scenario_1c_simple(): + + """ + tests a single insert and update; primary key is a date column + """ + + ctx = SessionContext() + + df = ctx.sql(f""" + select date '2021-01-01' as order_date, 'A' as order_type + union all + select date '2021-01-02' as order_date, 'A' as order_type + """).to_arrow_table() + + catalog = get_sql_catalog(_TEST_NAMESPACE) + table = catalog.create_table(f"{_TEST_NAMESPACE}.target", df.schema) + + table.append(df) + + source_df = ctx.sql(f""" + select date '2021-01-01' as order_date, 'A' as order_type + union all + select date '2021-01-02' as order_date, 'B' as order_type + union all + select date '2021-01-03' as order_date, 'A' as order_type + """).to_arrow_table() + + res = table.merge_rows(df=source_df, join_cols=["order_date"]) + + rows_updated_should_be = 1 + rows_inserted_should_be = 1 + + assert res['rows_updated'] == rows_updated_should_be, f"rows updated should be {rows_updated_should_be}, but got {res['rows_updated']}" + assert res['rows_inserted'] == rows_inserted_should_be, f"rows inserted should be {rows_inserted_should_be}, but got {res['rows_inserted']}" + + purge_warehouse() + print('merge rows: test scenario 1c (date as key column) pass') + +def test_merge_scenario_1d_simple(): + + """ + tests a single insert and update; primary key is a string column + """ + + ctx = SessionContext() + + df = ctx.sql(f""" + select 'abc' as order_id, 'A' as order_type + union all + select 'def' as order_id, 'A' as order_type + """).to_arrow_table() + + catalog = get_sql_catalog(_TEST_NAMESPACE) + table = catalog.create_table(f"{_TEST_NAMESPACE}.target", df.schema) + + table.append(df) + + source_df = ctx.sql(f""" + select 'abc' as order_id, 'A' as order_type + union all + select 'def' as order_id, 'B' as order_type + union all + select 'ghi' as order_id, 'A' as order_type + """).to_arrow_table() + + res = table.merge_rows(df=source_df, join_cols=["order_id"]) + + rows_updated_should_be = 1 + rows_inserted_should_be = 1 + + assert res['rows_updated'] == rows_updated_should_be, f"rows updated should be {rows_updated_should_be}, but got {res['rows_updated']}" + assert res['rows_inserted'] == rows_inserted_should_be, f"rows inserted should be {rows_inserted_should_be}, but got {res['rows_inserted']}" + + purge_warehouse() + print('merge rows: test scenario 1d (string as key column) pass') + +def test_merge_scenario_2_10k_rows(): + + """ + tests merging 10000 rows on a single key to simulate larger workload + """ + + ctx = SessionContext() + + table = gen_target_iceberg_table(1, 10000, False, ctx) + source_df = gen_source_dataset(5001, 15000, False, False, ctx) + + + res = table.merge_rows(df=source_df, join_cols=["order_id"]) + + rows_updated_should_be = 5000 + rows_inserted_should_be = 5000 + + assert res['rows_updated'] == rows_updated_should_be, f"rows updated should be {rows_updated_should_be}, but got {res['rows_updated']}" + assert res['rows_inserted'] == rows_inserted_should_be, f"rows inserted should be {rows_inserted_should_be}, but got {res['rows_inserted']}" + + purge_warehouse() Review Comment: i do not see this test_benchmark.py file anywhere. where is it located? -- This is an automated message from the Apache Git Service. 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