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[GLUTEN-1589][CH] support udf for clickhouse backend - #1596
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test hive udf |
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test python udf: #!/usr/bin/python3.7
import time
from pyspark import SparkConf
from pyspark.sql import SparkSession
from pyspark.sql.types import LongType
conf = SparkConf()
spark = SparkSession.builder.config(conf=conf).getOrCreate()
spark.sparkContext.setLogLevel("DEBUG")
# sc = SparkContext(conf=conf)
# spark = SparkSession.builder.master("local[1]").appName("test_udf").getOrCreate()
def my_add(x, y):
return x + y
def print_nothing(x):
pass
spark.udf.register("my_add", my_add, LongType())
start_time = time.time()
print(
spark.sql(
# "explain formatted select cast(id as String) from range(100)"
"explain formatted select my_add(id, 1) from range(1000000)"
).collect()
)
end_time = time.time()
time_cost = end_time - start_time
print("Time cost: ", time_cost) |
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@rui-mo velox failed with the same logs which appeared in other prs previously. Do you have time to take a look. |
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@taiyang-li Looks not relevant to this PR. Do we need to increase the memory limit? cc @zhztheplayer |
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please rebase |
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LGTM |
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What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
(Fixes: #1589)
除了支持udf之外,还解决了clickhouse中gtest和benchmark的编译失败问题。