H_2O-喷泡-2.4和Glue Jobs：{"error":"TypeError：'JavaPackage‘对象不可调用“，"errorType":"EXECUTION_FAILURE"}

Question

我试图使用pysparkling.ml.H2OMOJOModel来预测火花数据，使用h2o==3.32.0.2在AWS Glue Jobs中训练的MOJO模型，如何得到错误: TypeError：'JavaPackage‘对象不可调用。

我在AWS支持中打开了一张罚单，他们确认Glue环境很好，问题很可能是汽水(喷汽水)。似乎缺少了一些依赖库，但我不知道哪个库。如果我在本地计算机上运行(我只需要更改GBM_grid__1_AutoML_20220323_233606_model_53.zip)的mojo路径)，下面的简单代码就能很好地工作。

有谁能成功地在Glue jobs上使用闪闪发光的水呢？

工作详细信息：-Glue 2.0版-附加-python，H2O-pyfling-2.4=3.36.0.2-1 -Worker类型: G1.X -Number of -Worker:2 -Using脚本"createFromMojo.py“

createFromMojo.py：

import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job
import pandas as pd
from pysparkling.ml import H2OMOJOSettings
from pysparkling.ml import H2OMOJOModel
# from pysparkling.ml import *

## @params: [JOB_NAME]
args = getResolvedOptions(sys.argv, ["JOB_NAME"])

#Job setup
sc = SparkContext()
glueContext = GlueContext(sc)
spark = glueContext.spark_session

job = Job(glueContext)
job.init(args["JOB_NAME"], args)

caminho_modelo_mojo='s3://prod-lakehouse-stream/modeling/approaches/GBM_grid__1_AutoML_20220323_233606_model_53.zip'
print(caminho_modelo_mojo)
print(dir())

settings = H2OMOJOSettings(convertUnknownCategoricalLevelsToNa = True, convertInvalidNumbersToNa = True)
model = H2OMOJOModel.createFromMojo(caminho_modelo_mojo, settings)

data = {'days_since_last_application': [3, 2, 1, 0], 'job_area': ['a', 'b', 'c', 'd']}

base_escorada = model.transform(spark.createDataFrame(pd.DataFrame.from_dict(data)))

print(base_escorada.printSchema())

print(base_escorada.show())

job.commit()

Answer 1

我可以按照以下步骤成功地运行：

http://h2o-release.s3.amazonaws.com/sparkling-water/spark-3.1/3.36.1.1-1-3.1/index.html

• Dependent

• 下载了闪闪发光的水分发zip： JARs路径: s3://bucket_name/sparkling-water-assembly-scoring_2.12-3.36.1.1-1-3.1-all.jar

1. --additional-python-modules，h2o-pysparkling-3.1==3.36.1.1-1-3.1