[oalex] pasing the schema to avoid changing in confidence type
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20
strings.py
20
strings.py
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@ -23,6 +23,20 @@ matchings_schema = ArrayType(
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])
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)
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result_schema = StructType([
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StructField("affiliation", StringType(),nullable=True),
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StructField("match", ArrayType(
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StructType([
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StructField("Provenance", StringType(), nullable=True),
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StructField("PID", StringType(), nullable=True),
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StructField("Value", StringType(), nullable=True),
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StructField("Confidence", DoubleType(), nullable=True),
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StructField("Status", StringType(), nullable=True)
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])
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))
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])
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def oalex_affro_2(aff_string):
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try:
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matchings = affro(aff_string)
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@ -70,14 +84,14 @@ explode = spark.read.json(folder_path) \
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explode(col("raw_aff_string")).alias("affiliation") #this allows to split all the raw_aff_string and to parallelize better
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)
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affs = explode \
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rdd = explode \
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.select("affiliation") \
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.distinct() \
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.rdd \
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.flatMap(lambda row: [{"affiliation":row['affiliation'], "match": m} for m in oalex_affro(row['affiliation'])]).toDF()
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.flatMap(lambda row: [{"affiliation":row['affiliation'], "match": m} for m in oalex_affro(row['affiliation'])])
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#affs.map(json.dumps).saveAsTextFile("./out/rdd")
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affs = spark.createDataFrame(rdd, schema=result_schema)
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affs.join(explode, on="affiliation") \
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.select(col("DOI"),
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