mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-11-10 01:25:21 +00:00
316 lines
9.7 KiB
Python
316 lines
9.7 KiB
Python
import logging
|
|
import pytest
|
|
import os
|
|
import json
|
|
|
|
import helpers.client
|
|
from helpers.cluster import ClickHouseCluster, ClickHouseInstance
|
|
from helpers.test_tools import TSV
|
|
from helpers.s3_tools import prepare_s3_bucket, upload_directory, get_file_contents
|
|
|
|
import pyspark
|
|
from pyspark.sql.types import (
|
|
StructType,
|
|
StructField,
|
|
StringType,
|
|
IntegerType,
|
|
DateType,
|
|
TimestampType,
|
|
BooleanType,
|
|
ArrayType,
|
|
)
|
|
from pyspark.sql.functions import current_timestamp
|
|
from datetime import datetime
|
|
from pyspark.sql.functions import monotonically_increasing_id, row_number
|
|
from pyspark.sql.window import Window
|
|
|
|
|
|
SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))
|
|
|
|
|
|
def get_spark():
|
|
builder = (
|
|
pyspark.sql.SparkSession.builder.appName("spark_test")
|
|
.config(
|
|
"org.apache.spark.sql.hudi.catalog.HoodieCatalog",
|
|
)
|
|
.config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
|
|
.config(
|
|
"spark.sql.catalog.local", "org.apache.spark.sql.hudi.catalog.HoodieCatalog"
|
|
)
|
|
.config("spark.driver.memory", "20g")
|
|
.master("local")
|
|
)
|
|
return builder.getOrCreate()
|
|
|
|
|
|
@pytest.fixture(scope="module")
|
|
def started_cluster():
|
|
cluster = ClickHouseCluster(__file__, with_spark=True)
|
|
try:
|
|
cluster.add_instance(
|
|
"node1",
|
|
main_configs=["configs/config.d/named_collections.xml"],
|
|
user_configs=["configs/users.d/users.xml"],
|
|
with_minio=True,
|
|
)
|
|
|
|
logging.info("Starting cluster...")
|
|
cluster.start()
|
|
|
|
prepare_s3_bucket(cluster)
|
|
logging.info("S3 bucket created")
|
|
|
|
cluster.spark_session = get_spark()
|
|
|
|
yield cluster
|
|
|
|
finally:
|
|
cluster.shutdown()
|
|
|
|
|
|
def run_query(instance, query, stdin=None, settings=None):
|
|
# type: (ClickHouseInstance, str, object, dict) -> str
|
|
|
|
logging.info("Running query '{}'...".format(query))
|
|
result = instance.query(query, stdin=stdin, settings=settings)
|
|
logging.info("Query finished")
|
|
|
|
return result
|
|
|
|
|
|
def write_hudi_from_df(spark, table_name, df, result_path, mode="overwrite"):
|
|
if mode == "overwrite":
|
|
hudi_write_mode = "insert_overwrite"
|
|
else:
|
|
hudi_write_mode = "upsert"
|
|
|
|
df.write.mode(mode).option("compression", "none").option(
|
|
"compression", "none"
|
|
).format("hudi").option("hoodie.table.name", table_name).option(
|
|
"hoodie.datasource.write.partitionpath.field", "partitionpath"
|
|
).option(
|
|
"hoodie.datasource.write.table.name", table_name
|
|
).option(
|
|
"hoodie.datasource.write.operation", hudi_write_mode
|
|
).option(
|
|
"hoodie.datasource.compaction.async.enable", "true"
|
|
).option(
|
|
"hoodie.compact.inline", "false"
|
|
).option(
|
|
"hoodie.compact.inline.max.delta.commits", "10"
|
|
).option(
|
|
"hoodie.parquet.compression.codec", "snappy"
|
|
).option(
|
|
"hoodie.hfile.compression.algorithm", "uncompressed"
|
|
).option(
|
|
"hoodie.datasource.write.recordkey.field", "a"
|
|
).option(
|
|
"hoodie.datasource.write.precombine.field", "a"
|
|
).save(
|
|
result_path
|
|
)
|
|
|
|
|
|
def write_hudi_from_file(spark, table_name, path, result_path):
|
|
spark.conf.set("spark.sql.debug.maxToStringFields", 100000)
|
|
df = spark.read.load(f"file://{path}")
|
|
write_hudi_from_df(spark, table_name, df, result_path)
|
|
|
|
|
|
def generate_data(spark, start, end, append=1):
|
|
a = spark.range(start, end, 1).toDF("a")
|
|
b = spark.range(start + append, end + append, 1).toDF("b")
|
|
b = b.withColumn("b", b["b"].cast(StringType()))
|
|
|
|
a = a.withColumn(
|
|
"row_index", row_number().over(Window.orderBy(monotonically_increasing_id()))
|
|
)
|
|
b = b.withColumn(
|
|
"row_index", row_number().over(Window.orderBy(monotonically_increasing_id()))
|
|
)
|
|
|
|
df = a.join(b, on=["row_index"]).drop("row_index")
|
|
return df
|
|
|
|
|
|
def create_hudi_table(node, table_name):
|
|
node.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS {table_name};
|
|
CREATE TABLE {table_name}
|
|
ENGINE=Hudi(s3, filename = '{table_name}/')"""
|
|
)
|
|
|
|
|
|
def create_initial_data_file(
|
|
cluster, node, query, table_name, compression_method="none"
|
|
):
|
|
node.query(
|
|
f"""
|
|
INSERT INTO TABLE FUNCTION
|
|
file('{table_name}.parquet')
|
|
SETTINGS
|
|
output_format_parquet_compression_method='{compression_method}',
|
|
s3_truncate_on_insert=1 {query}
|
|
FORMAT Parquet"""
|
|
)
|
|
user_files_path = os.path.join(
|
|
SCRIPT_DIR, f"{cluster.instances_dir_name}/node1/database/user_files"
|
|
)
|
|
result_path = f"{user_files_path}/{table_name}.parquet"
|
|
return result_path
|
|
|
|
|
|
def test_single_hudi_file(started_cluster):
|
|
instance = started_cluster.instances["node1"]
|
|
spark = started_cluster.spark_session
|
|
minio_client = started_cluster.minio_client
|
|
bucket = started_cluster.minio_bucket
|
|
TABLE_NAME = "test_single_hudi_file"
|
|
|
|
inserted_data = "SELECT number as a, toString(number) as b FROM numbers(100)"
|
|
parquet_data_path = create_initial_data_file(
|
|
started_cluster, instance, inserted_data, TABLE_NAME
|
|
)
|
|
|
|
write_hudi_from_file(spark, TABLE_NAME, parquet_data_path, f"/{TABLE_NAME}")
|
|
files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
|
|
assert len(files) == 1
|
|
assert files[0].endswith(".parquet")
|
|
|
|
create_hudi_table(instance, TABLE_NAME)
|
|
assert instance.query(f"SELECT a, b FROM {TABLE_NAME}") == instance.query(
|
|
inserted_data
|
|
)
|
|
|
|
|
|
def test_multiple_hudi_files(started_cluster):
|
|
instance = started_cluster.instances["node1"]
|
|
spark = started_cluster.spark_session
|
|
minio_client = started_cluster.minio_client
|
|
bucket = started_cluster.minio_bucket
|
|
TABLE_NAME = "test_multiple_hudi_files"
|
|
|
|
write_hudi_from_df(
|
|
spark, TABLE_NAME, generate_data(spark, 0, 100), f"/{TABLE_NAME}"
|
|
)
|
|
files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
|
|
assert len(files) == 1
|
|
|
|
create_hudi_table(instance, TABLE_NAME)
|
|
assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 100
|
|
|
|
write_hudi_from_df(
|
|
spark,
|
|
TABLE_NAME,
|
|
generate_data(spark, 100, 200),
|
|
f"/{TABLE_NAME}",
|
|
mode="append",
|
|
)
|
|
files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
|
|
assert len(files) == 2
|
|
|
|
assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 200
|
|
assert instance.query(
|
|
f"SELECT a, b FROM {TABLE_NAME} ORDER BY 1"
|
|
) == instance.query("SELECT number, toString(number + 1) FROM numbers(200)")
|
|
|
|
write_hudi_from_df(
|
|
spark,
|
|
TABLE_NAME,
|
|
generate_data(spark, 100, 300),
|
|
f"/{TABLE_NAME}",
|
|
mode="append",
|
|
)
|
|
files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
|
|
assert len(files) == 3
|
|
|
|
assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 300
|
|
assert instance.query(
|
|
f"SELECT a, b FROM {TABLE_NAME} ORDER BY 1"
|
|
) == instance.query("SELECT number, toString(number + 1) FROM numbers(300)")
|
|
|
|
assert int(instance.query(f"SELECT b FROM {TABLE_NAME} WHERE a = 100")) == 101
|
|
write_hudi_from_df(
|
|
spark,
|
|
TABLE_NAME,
|
|
generate_data(spark, 100, 101, append=0),
|
|
f"/{TABLE_NAME}",
|
|
mode="append",
|
|
)
|
|
files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
|
|
|
|
assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 300
|
|
assert int(instance.query(f"SELECT b FROM {TABLE_NAME} WHERE a = 100")) == 100
|
|
|
|
write_hudi_from_df(
|
|
spark,
|
|
TABLE_NAME,
|
|
generate_data(spark, 100, 1000000, append=0),
|
|
f"/{TABLE_NAME}",
|
|
mode="append",
|
|
)
|
|
files = upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
|
|
assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 1000000
|
|
|
|
|
|
def test_types(started_cluster):
|
|
instance = started_cluster.instances["node1"]
|
|
spark = started_cluster.spark_session
|
|
minio_client = started_cluster.minio_client
|
|
bucket = started_cluster.minio_bucket
|
|
TABLE_NAME = "test_types"
|
|
|
|
data = [
|
|
(
|
|
123,
|
|
"string",
|
|
datetime.strptime("2000-01-01", "%Y-%m-%d"),
|
|
["str1", "str2"],
|
|
True,
|
|
)
|
|
]
|
|
schema = StructType(
|
|
[
|
|
StructField("a", IntegerType()),
|
|
StructField("b", StringType()),
|
|
StructField("c", DateType()),
|
|
StructField("d", ArrayType(StringType())),
|
|
StructField("e", BooleanType()),
|
|
]
|
|
)
|
|
df = spark.createDataFrame(data=data, schema=schema)
|
|
df.printSchema()
|
|
write_hudi_from_df(spark, TABLE_NAME, df, f"/{TABLE_NAME}", mode="overwrite")
|
|
|
|
upload_directory(minio_client, bucket, f"/{TABLE_NAME}", "")
|
|
|
|
create_hudi_table(instance, TABLE_NAME)
|
|
assert int(instance.query(f"SELECT count() FROM {TABLE_NAME}")) == 1
|
|
assert (
|
|
instance.query(f"SELECT a, b, c, d, e FROM {TABLE_NAME}").strip()
|
|
== "123\tstring\t2000-01-01\t['str1','str2']\ttrue"
|
|
)
|
|
|
|
table_function = f"hudi(s3, filename='{TABLE_NAME}/')"
|
|
assert (
|
|
instance.query(f"SELECT a, b, c, d, e FROM {table_function}").strip()
|
|
== "123\tstring\t2000-01-01\t['str1','str2']\ttrue"
|
|
)
|
|
|
|
assert instance.query(f"DESCRIBE {table_function} FORMAT TSV") == TSV(
|
|
[
|
|
["_hoodie_commit_time", "Nullable(String)"],
|
|
["_hoodie_commit_seqno", "Nullable(String)"],
|
|
["_hoodie_record_key", "Nullable(String)"],
|
|
["_hoodie_partition_path", "Nullable(String)"],
|
|
["_hoodie_file_name", "Nullable(String)"],
|
|
["a", "Nullable(Int32)"],
|
|
["b", "Nullable(String)"],
|
|
["c", "Nullable(Date32)"],
|
|
["d", "Array(Nullable(String))"],
|
|
["e", "Nullable(Bool)"],
|
|
]
|
|
)
|