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https://github.com/ClickHouse/ClickHouse.git
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712 lines
21 KiB
Python
712 lines
21 KiB
Python
import helpers.client
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from helpers.cluster import ClickHouseCluster
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from helpers.test_tools import TSV
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import pytest
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import logging
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import os
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import json
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import time
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import glob
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import pyspark
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import delta
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from delta import *
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from pyspark.sql.types import (
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StructType,
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StructField,
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StringType,
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IntegerType,
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DateType,
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TimestampType,
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BooleanType,
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ArrayType,
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)
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from pyspark.sql.functions import current_timestamp
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from datetime import datetime
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from pyspark.sql.functions import monotonically_increasing_id, row_number
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from pyspark.sql.window import Window
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from minio.deleteobjects import DeleteObject
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from helpers.s3_tools import (
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prepare_s3_bucket,
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upload_directory,
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get_file_contents,
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list_s3_objects,
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)
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SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))
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def get_spark():
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builder = (
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pyspark.sql.SparkSession.builder.appName("spark_test")
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.config("spark.sql.extensions", "io.delta.sql.DeltaSparkSessionExtension")
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.config(
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"spark.sql.catalog.spark_catalog",
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"org.apache.spark.sql.delta.catalog.DeltaCatalog",
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)
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.master("local")
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)
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return builder.master("local").getOrCreate()
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@pytest.fixture(scope="module")
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def started_cluster():
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try:
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cluster = ClickHouseCluster(__file__, with_spark=True)
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cluster.add_instance(
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"node1",
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main_configs=["configs/config.d/named_collections.xml"],
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user_configs=["configs/users.d/users.xml"],
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with_minio=True,
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stay_alive=True,
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)
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logging.info("Starting cluster...")
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cluster.start()
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prepare_s3_bucket(cluster)
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cluster.spark_session = get_spark()
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yield cluster
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finally:
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cluster.shutdown()
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def write_delta_from_file(spark, path, result_path, mode="overwrite"):
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spark.read.load(path).write.mode(mode).option("compression", "none").format(
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"delta"
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).option("delta.columnMapping.mode", "name").save(result_path)
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def write_delta_from_df(spark, df, result_path, mode="overwrite", partition_by=None):
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if partition_by is None:
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df.write.mode(mode).option("compression", "none").format("delta").option(
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"delta.columnMapping.mode", "name"
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).save(result_path)
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else:
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df.write.mode(mode).option("compression", "none").format("delta").option(
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"delta.columnMapping.mode", "name"
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).partitionBy("a").save(result_path)
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def generate_data(spark, start, end):
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a = spark.range(start, end, 1).toDF("a")
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b = spark.range(start + 1, end + 1, 1).toDF("b")
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b = b.withColumn("b", b["b"].cast(StringType()))
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a = a.withColumn(
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"row_index", row_number().over(Window.orderBy(monotonically_increasing_id()))
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)
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b = b.withColumn(
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"row_index", row_number().over(Window.orderBy(monotonically_increasing_id()))
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)
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df = a.join(b, on=["row_index"]).drop("row_index")
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return df
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def get_delta_metadata(delta_metadata_file):
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jsons = [json.loads(x) for x in delta_metadata_file.splitlines()]
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combined_json = {}
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for d in jsons:
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combined_json.update(d)
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return combined_json
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def create_delta_table(node, table_name, bucket="root"):
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node.query(
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f"""
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DROP TABLE IF EXISTS {table_name};
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CREATE TABLE {table_name}
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ENGINE=DeltaLake(s3, filename = '{table_name}/', url = 'http://minio1:9001/{bucket}/')"""
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)
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def create_initial_data_file(
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cluster, node, query, table_name, compression_method="none"
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):
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node.query(
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f"""
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INSERT INTO TABLE FUNCTION
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file('{table_name}.parquet')
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SETTINGS
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output_format_parquet_compression_method='{compression_method}',
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s3_truncate_on_insert=1 {query}
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FORMAT Parquet"""
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)
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user_files_path = os.path.join(
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SCRIPT_DIR, f"{cluster.instances_dir_name}/node1/database/user_files"
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)
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result_path = f"{user_files_path}/{table_name}.parquet"
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return result_path
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def test_single_log_file(started_cluster):
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instance = started_cluster.instances["node1"]
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spark = started_cluster.spark_session
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minio_client = started_cluster.minio_client
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bucket = started_cluster.minio_bucket
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TABLE_NAME = "test_single_log_file"
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inserted_data = "SELECT number as a, toString(number + 1) as b FROM numbers(100)"
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parquet_data_path = create_initial_data_file(
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started_cluster, instance, inserted_data, TABLE_NAME
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)
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write_delta_from_file(spark, parquet_data_path, f"/{TABLE_NAME}")
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files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
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assert len(files) == 2 # 1 metadata files + 1 data file
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create_delta_table(instance, TABLE_NAME)
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assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 100
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assert instance.query(f"SELECT * FROM {TABLE_NAME}") == instance.query(
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inserted_data
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)
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def test_partition_by(started_cluster):
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instance = started_cluster.instances["node1"]
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spark = started_cluster.spark_session
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minio_client = started_cluster.minio_client
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bucket = started_cluster.minio_bucket
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TABLE_NAME = "test_partition_by"
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write_delta_from_df(
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spark,
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generate_data(spark, 0, 10),
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f"/{TABLE_NAME}",
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mode="overwrite",
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partition_by="a",
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)
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files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
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assert len(files) == 11 # 10 partitions and 1 metadata file
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create_delta_table(instance, TABLE_NAME)
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assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 10
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def test_checkpoint(started_cluster):
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instance = started_cluster.instances["node1"]
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spark = started_cluster.spark_session
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minio_client = started_cluster.minio_client
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bucket = started_cluster.minio_bucket
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TABLE_NAME = "test_checkpoint"
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write_delta_from_df(
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spark,
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generate_data(spark, 0, 1),
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f"/{TABLE_NAME}",
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mode="overwrite",
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)
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for i in range(1, 25):
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write_delta_from_df(
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spark,
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generate_data(spark, i, i + 1),
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f"/{TABLE_NAME}",
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mode="append",
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)
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files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
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# 25 data files
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# 25 metadata files
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# 1 last_metadata file
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# 2 checkpoints
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assert len(files) == 25 * 2 + 3
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ok = False
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for file in files:
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if file.endswith("last_checkpoint"):
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ok = True
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assert ok
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create_delta_table(instance, TABLE_NAME)
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assert (
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int(
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instance.query(
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f"SELECT count() FROM {TABLE_NAME} SETTINGS input_format_parquet_allow_missing_columns=1"
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)
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)
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== 25
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)
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table = DeltaTable.forPath(spark, f"/{TABLE_NAME}")
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table.delete("a < 10")
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files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
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assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 15
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for i in range(0, 5):
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write_delta_from_df(
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spark,
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generate_data(spark, i, i + 1),
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f"/{TABLE_NAME}",
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mode="append",
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)
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# + 1 metadata files (for delete)
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# + 5 data files
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# + 5 metadata files
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# + 1 checkpoint file
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# + 1 ?
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files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
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assert len(files) == 53 + 1 + 5 * 2 + 1 + 1
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assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 20
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assert (
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instance.query(f"SELECT * FROM {TABLE_NAME} ORDER BY 1").strip()
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== instance.query(
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"SELECT * FROM ("
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"SELECT number, toString(number + 1) FROM numbers(5) "
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"UNION ALL SELECT number, toString(number + 1) FROM numbers(10, 15) "
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") ORDER BY 1"
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).strip()
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)
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def test_multiple_log_files(started_cluster):
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instance = started_cluster.instances["node1"]
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spark = started_cluster.spark_session
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minio_client = started_cluster.minio_client
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bucket = started_cluster.minio_bucket
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TABLE_NAME = "test_multiple_log_files"
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write_delta_from_df(
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spark, generate_data(spark, 0, 100), f"/{TABLE_NAME}", mode="overwrite"
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)
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files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
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assert len(files) == 2 # 1 metadata files + 1 data file
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s3_objects = list(
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minio_client.list_objects(bucket, f"{TABLE_NAME}/_delta_log/", recursive=True)
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)
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assert len(s3_objects) == 1
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create_delta_table(instance, TABLE_NAME)
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assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 100
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write_delta_from_df(
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spark, generate_data(spark, 100, 200), f"/{TABLE_NAME}", mode="append"
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)
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files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
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assert len(files) == 4 # 2 metadata files + 2 data files
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s3_objects = list(
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minio_client.list_objects(bucket, f"{TABLE_NAME}/_delta_log/", recursive=True)
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)
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assert len(s3_objects) == 2
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assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 200
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assert instance.query(f"SELECT * FROM {TABLE_NAME} ORDER BY 1") == instance.query(
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"SELECT number, toString(number + 1) FROM numbers(200)"
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)
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def test_metadata(started_cluster):
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instance = started_cluster.instances["node1"]
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spark = started_cluster.spark_session
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minio_client = started_cluster.minio_client
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bucket = started_cluster.minio_bucket
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TABLE_NAME = "test_metadata"
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parquet_data_path = create_initial_data_file(
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started_cluster,
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instance,
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"SELECT number, toString(number) FROM numbers(100)",
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TABLE_NAME,
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)
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write_delta_from_file(spark, parquet_data_path, f"/{TABLE_NAME}")
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upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
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data = get_file_contents(
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minio_client,
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bucket,
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f"/{TABLE_NAME}/_delta_log/00000000000000000000.json",
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)
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delta_metadata = get_delta_metadata(data)
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stats = json.loads(delta_metadata["add"]["stats"])
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assert stats["numRecords"] == 100
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assert next(iter(stats["minValues"].values())) == 0
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assert next(iter(stats["maxValues"].values())) == 99
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create_delta_table(instance, TABLE_NAME)
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assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 100
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def test_types(started_cluster):
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TABLE_NAME = "test_types"
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spark = started_cluster.spark_session
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result_file = f"{TABLE_NAME}_result_2"
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delta_table = (
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DeltaTable.create(spark)
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.tableName(TABLE_NAME)
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.location(f"/{result_file}")
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.addColumn("a", "INT")
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.addColumn("b", "STRING")
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.addColumn("c", "DATE")
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.addColumn("d", "ARRAY<STRING>")
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.addColumn("e", "BOOLEAN")
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.execute()
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)
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data = [
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(
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123,
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"string",
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datetime.strptime("2000-01-01", "%Y-%m-%d"),
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["str1", "str2"],
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True,
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)
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]
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schema = StructType(
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[
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StructField("a", IntegerType()),
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StructField("b", StringType()),
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StructField("c", DateType()),
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StructField("d", ArrayType(StringType())),
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StructField("e", BooleanType()),
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]
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)
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df = spark.createDataFrame(data=data, schema=schema)
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df.printSchema()
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df.write.mode("append").format("delta").saveAsTable(TABLE_NAME)
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minio_client = started_cluster.minio_client
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bucket = started_cluster.minio_bucket
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upload_directory(minio_client, bucket, f"/{result_file}", "")
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instance = started_cluster.instances["node1"]
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instance.query(
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f"""
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DROP TABLE IF EXISTS {TABLE_NAME};
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CREATE TABLE {TABLE_NAME} ENGINE=DeltaLake('http://{started_cluster.minio_ip}:{started_cluster.minio_port}/{bucket}/{result_file}/', 'minio', 'minio123')"""
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)
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assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 1
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assert (
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instance.query(f"SELECT * FROM {TABLE_NAME}").strip()
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== "123\tstring\t2000-01-01\t['str1','str2']\ttrue"
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)
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table_function = f"deltaLake('http://{started_cluster.minio_ip}:{started_cluster.minio_port}/{bucket}/{result_file}/', 'minio', 'minio123')"
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assert (
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instance.query(f"SELECT * FROM {table_function}").strip()
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== "123\tstring\t2000-01-01\t['str1','str2']\ttrue"
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)
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assert instance.query(f"DESCRIBE {table_function} FORMAT TSV") == TSV(
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[
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["a", "Nullable(Int32)"],
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["b", "Nullable(String)"],
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["c", "Nullable(Date32)"],
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["d", "Array(Nullable(String))"],
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["e", "Nullable(Bool)"],
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]
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)
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def test_restart_broken(started_cluster):
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instance = started_cluster.instances["node1"]
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spark = started_cluster.spark_session
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minio_client = started_cluster.minio_client
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bucket = "broken"
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TABLE_NAME = "test_restart_broken"
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if not minio_client.bucket_exists(bucket):
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minio_client.make_bucket(bucket)
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parquet_data_path = create_initial_data_file(
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started_cluster,
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instance,
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"SELECT number, toString(number) FROM numbers(100)",
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TABLE_NAME,
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)
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write_delta_from_file(spark, parquet_data_path, f"/{TABLE_NAME}")
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upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
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create_delta_table(instance, TABLE_NAME, bucket=bucket)
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assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 100
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s3_objects = list_s3_objects(minio_client, bucket, prefix="")
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assert (
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len(
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list(
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minio_client.remove_objects(
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bucket,
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[DeleteObject(obj) for obj in s3_objects],
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)
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)
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)
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== 0
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)
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minio_client.remove_bucket(bucket)
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instance.restart_clickhouse()
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assert "NoSuchBucket" in instance.query_and_get_error(
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f"SELECT count() FROM {TABLE_NAME}"
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)
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minio_client.make_bucket(bucket)
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upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
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assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 100
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def test_restart_broken_table_function(started_cluster):
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instance = started_cluster.instances["node1"]
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spark = started_cluster.spark_session
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minio_client = started_cluster.minio_client
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bucket = "broken2"
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TABLE_NAME = "test_restart_broken_table_function"
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if not minio_client.bucket_exists(bucket):
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minio_client.make_bucket(bucket)
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parquet_data_path = create_initial_data_file(
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started_cluster,
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instance,
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"SELECT number, toString(number) FROM numbers(100)",
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TABLE_NAME,
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)
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write_delta_from_file(spark, parquet_data_path, f"/{TABLE_NAME}")
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upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
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instance.query(
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f"""
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DROP TABLE IF EXISTS {TABLE_NAME};
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CREATE TABLE {TABLE_NAME}
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AS deltaLake(s3, filename = '{TABLE_NAME}/', url = 'http://minio1:9001/{bucket}/')"""
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)
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assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 100
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s3_objects = list_s3_objects(minio_client, bucket, prefix="")
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assert (
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len(
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list(
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minio_client.remove_objects(
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bucket,
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[DeleteObject(obj) for obj in s3_objects],
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)
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)
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)
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== 0
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)
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minio_client.remove_bucket(bucket)
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instance.restart_clickhouse()
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assert "NoSuchBucket" in instance.query_and_get_error(
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f"SELECT count() FROM {TABLE_NAME}"
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)
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minio_client.make_bucket(bucket)
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upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
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assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 100
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def test_partition_columns(started_cluster):
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instance = started_cluster.instances["node1"]
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spark = started_cluster.spark_session
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minio_client = started_cluster.minio_client
|
|
bucket = started_cluster.minio_bucket
|
|
TABLE_NAME = "test_partition_columns"
|
|
result_file = f"{TABLE_NAME}"
|
|
partition_columns = ["b", "c", "d", "e"]
|
|
|
|
delta_table = (
|
|
DeltaTable.create(spark)
|
|
.tableName(TABLE_NAME)
|
|
.location(f"/{result_file}")
|
|
.addColumn("a", "INT")
|
|
.addColumn("b", "STRING")
|
|
.addColumn("c", "DATE")
|
|
.addColumn("d", "INT")
|
|
.addColumn("e", "BOOLEAN")
|
|
.partitionedBy(partition_columns)
|
|
.execute()
|
|
)
|
|
num_rows = 9
|
|
|
|
schema = StructType(
|
|
[
|
|
StructField("a", IntegerType()),
|
|
StructField("b", StringType()),
|
|
StructField("c", DateType()),
|
|
StructField("d", IntegerType()),
|
|
StructField("e", BooleanType()),
|
|
]
|
|
)
|
|
|
|
for i in range(1, num_rows + 1):
|
|
data = [
|
|
(
|
|
i,
|
|
"test" + str(i),
|
|
datetime.strptime(f"2000-01-0{i}", "%Y-%m-%d"),
|
|
i,
|
|
False,
|
|
)
|
|
]
|
|
df = spark.createDataFrame(data=data, schema=schema)
|
|
df.printSchema()
|
|
df.write.mode("append").format("delta").partitionBy(partition_columns).save(
|
|
f"/{TABLE_NAME}"
|
|
)
|
|
|
|
minio_client = started_cluster.minio_client
|
|
bucket = started_cluster.minio_bucket
|
|
|
|
files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
|
|
assert len(files) > 0
|
|
print(f"Uploaded files: {files}")
|
|
|
|
result = instance.query(
|
|
f"describe table deltaLake('http://{started_cluster.minio_ip}:{started_cluster.minio_port}/{bucket}/{result_file}/', 'minio', 'minio123')"
|
|
).strip()
|
|
|
|
assert (
|
|
result
|
|
== "a\tNullable(Int32)\t\t\t\t\t\nb\tNullable(String)\t\t\t\t\t\nc\tNullable(Date32)\t\t\t\t\t\nd\tNullable(Int32)\t\t\t\t\t\ne\tNullable(Bool)"
|
|
)
|
|
|
|
result = int(
|
|
instance.query(
|
|
f"""SELECT count()
|
|
FROM deltaLake('http://{started_cluster.minio_ip}:{started_cluster.minio_port}/{bucket}/{result_file}/', 'minio', 'minio123')
|
|
"""
|
|
)
|
|
)
|
|
assert result == num_rows
|
|
result = int(
|
|
instance.query(
|
|
f"""SELECT count()
|
|
FROM deltaLake('http://{started_cluster.minio_ip}:{started_cluster.minio_port}/{bucket}/{result_file}/', 'minio', 'minio123')
|
|
WHERE c == toDateTime('2000/01/05')
|
|
"""
|
|
)
|
|
)
|
|
assert result == 1
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS {TABLE_NAME};
|
|
CREATE TABLE {TABLE_NAME} (a Nullable(Int32), b Nullable(String), c Nullable(Date32), d Nullable(Int32), e Nullable(Bool))
|
|
ENGINE=DeltaLake('http://{started_cluster.minio_ip}:{started_cluster.minio_port}/{bucket}/{result_file}/', 'minio', 'minio123')"""
|
|
)
|
|
assert (
|
|
"""1 test1 2000-01-01 1 false
|
|
2 test2 2000-01-02 2 false
|
|
3 test3 2000-01-03 3 false
|
|
4 test4 2000-01-04 4 false
|
|
5 test5 2000-01-05 5 false
|
|
6 test6 2000-01-06 6 false
|
|
7 test7 2000-01-07 7 false
|
|
8 test8 2000-01-08 8 false
|
|
9 test9 2000-01-09 9 false"""
|
|
== instance.query(f"SELECT * FROM {TABLE_NAME} ORDER BY b").strip()
|
|
)
|
|
|
|
assert (
|
|
int(
|
|
instance.query(
|
|
f"SELECT count() FROM {TABLE_NAME} WHERE c == toDateTime('2000/01/05')"
|
|
)
|
|
)
|
|
== 1
|
|
)
|
|
|
|
# Subset of columns should work.
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS {TABLE_NAME};
|
|
CREATE TABLE {TABLE_NAME} (b Nullable(String), c Nullable(Date32), d Nullable(Int32))
|
|
ENGINE=DeltaLake('http://{started_cluster.minio_ip}:{started_cluster.minio_port}/{bucket}/{result_file}/', 'minio', 'minio123')"""
|
|
)
|
|
assert (
|
|
"""test1 2000-01-01 1
|
|
test2 2000-01-02 2
|
|
test3 2000-01-03 3
|
|
test4 2000-01-04 4
|
|
test5 2000-01-05 5
|
|
test6 2000-01-06 6
|
|
test7 2000-01-07 7
|
|
test8 2000-01-08 8
|
|
test9 2000-01-09 9"""
|
|
== instance.query(f"SELECT * FROM {TABLE_NAME} ORDER BY b").strip()
|
|
)
|
|
|
|
for i in range(num_rows + 1, 2 * num_rows + 1):
|
|
data = [
|
|
(
|
|
i,
|
|
"test" + str(i),
|
|
datetime.strptime(f"2000-01-{i}", "%Y-%m-%d"),
|
|
i,
|
|
False,
|
|
)
|
|
]
|
|
df = spark.createDataFrame(data=data, schema=schema)
|
|
df.printSchema()
|
|
df.write.mode("append").format("delta").partitionBy(partition_columns).save(
|
|
f"/{TABLE_NAME}"
|
|
)
|
|
|
|
files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
|
|
ok = False
|
|
for file in files:
|
|
if file.endswith("last_checkpoint"):
|
|
ok = True
|
|
assert ok
|
|
|
|
result = int(
|
|
instance.query(
|
|
f"""SELECT count()
|
|
FROM deltaLake('http://{started_cluster.minio_ip}:{started_cluster.minio_port}/{bucket}/{result_file}/', 'minio', 'minio123')
|
|
"""
|
|
)
|
|
)
|
|
assert result == num_rows * 2
|
|
|
|
assert (
|
|
"""1 test1 2000-01-01 1 false
|
|
2 test2 2000-01-02 2 false
|
|
3 test3 2000-01-03 3 false
|
|
4 test4 2000-01-04 4 false
|
|
5 test5 2000-01-05 5 false
|
|
6 test6 2000-01-06 6 false
|
|
7 test7 2000-01-07 7 false
|
|
8 test8 2000-01-08 8 false
|
|
9 test9 2000-01-09 9 false
|
|
10 test10 2000-01-10 10 false
|
|
11 test11 2000-01-11 11 false
|
|
12 test12 2000-01-12 12 false
|
|
13 test13 2000-01-13 13 false
|
|
14 test14 2000-01-14 14 false
|
|
15 test15 2000-01-15 15 false
|
|
16 test16 2000-01-16 16 false
|
|
17 test17 2000-01-17 17 false
|
|
18 test18 2000-01-18 18 false"""
|
|
== instance.query(
|
|
f"""
|
|
SELECT * FROM deltaLake('http://{started_cluster.minio_ip}:{started_cluster.minio_port}/{bucket}/{result_file}/', 'minio', 'minio123') ORDER BY c
|
|
"""
|
|
).strip()
|
|
)
|
|
assert (
|
|
int(
|
|
instance.query(
|
|
f"SELECT count() FROM {TABLE_NAME} WHERE c == toDateTime('2000/01/15')"
|
|
)
|
|
)
|
|
== 1
|
|
)
|