在 spark 中读取 XML

Question

我正在尝试使用 spark-xml jar 在 pyspark 中读取 xml/nested xml。

df = sqlContext.read \
  .format("com.databricks.spark.xml")\
   .option("rowTag", "hierachy")\
   .load("test.xml"

当我执行时，数据框没有正确创建。

    +--------------------+
    |                 att|
    +--------------------+
    |[[1,Data,[Wrapped...|
    +--------------------+

xml 我的格式如下：

Answer 1

heirarchy 应该是 rootTag 而 att 应该是 rowTag 作为

df = spark.read \
    .format("com.databricks.spark.xml") \
    .option("rootTag", "hierarchy") \
    .option("rowTag", "att") \
    .load("test.xml")

你应该得到

+-----+------+----------------------------+
|Order|attval|children                    |
+-----+------+----------------------------+
|1    |Data  |[[[1, Studyval], [2, Site]]]|
|2    |Info  |[[[1, age], [2, gender]]]   |
+-----+------+----------------------------+

和schema

root
 |-- Order: long (nullable = true)
 |-- attval: string (nullable = true)
 |-- children: struct (nullable = true)
 |    |-- att: array (nullable = true)
 |    |    |-- element: struct (containsNull = true)
 |    |    |    |-- Order: long (nullable = true)
 |    |    |    |-- attval: string (nullable = true)

查找有关 databricks xml

的更多信息

Answer 2

Databricks 已发布新版本以读取 xml 到 Spark DataFrame

<dependency>
     <groupId>com.databricks</groupId>
     <artifactId>spark-xml_2.12</artifactId>
     <version>0.6.0</version>
 </dependency>

我在此示例中使用的输入 XML 文件可在 GitHub 存储库中获得。

val df = spark.read
      .format("com.databricks.spark.xml")
      .option("rowTag", "person")
      .xml("persons.xml")

架构

root
 |-- _id: long (nullable = true)
 |-- dob_month: long (nullable = true)
 |-- dob_year: long (nullable = true)
 |-- firstname: string (nullable = true)
 |-- gender: string (nullable = true)
 |-- lastname: string (nullable = true)
 |-- middlename: string (nullable = true)
 |-- salary: struct (nullable = true)
 |    |-- _VALUE: long (nullable = true)
 |    |-- _currency: string (nullable = true)

输出：

+---+---------+--------+---------+------+--------+----------+---------------+
|_id|dob_month|dob_year|firstname|gender|lastname|middlename|         salary|
+---+---------+--------+---------+------+--------+----------+---------------+
|  1|        1|    1980|    James|     M|   Smith|      null|  [10000, Euro]|
|  2|        6|    1990|  Michael|     M|    null|      Rose|[10000, Dollor]|
+---+---------+--------+---------+------+--------+----------+---------------+

请注意 Spark XML API 有一些限制并在此处讨论 Spark-XML API Limitations

希望对您有所帮助！！

Answer 3

您可以使用 Databricks jar 将 xml 解析为数据帧。可以使用maven或者sbt编译依赖也可以直接使用spark submit的jar

pyspark --jars /home/sandipan/Downloads/spark_jars/spark-xml_2.11-0.6.0.jar

df = spark.read \
    .format("com.databricks.spark.xml") \
    .option("rootTag", "SmsRecords") \
    .option("rowTag", "sms") \
    .load("/home/sandipan/Downloads/mySMS/Sms/backupinfo.xml")

Schema>>> df.printSchema()
root
 |-- address: string (nullable = true)
 |-- body: string (nullable = true)
 |-- date: long (nullable = true)
 |-- type: long (nullable = true)

>>> df.select("address").distinct().count()
530

关注这个 http://www.thehadoopguy.com/2019/09/how-to-parse-xml-data-to-saprk-dataframe.html

在 spark 中读取 XML

Read XML in spark

xml

apache-spark

dataframe

pyspark

apache-spark-xml