columnNameOfCorruptRecord: The name of new field where malformed strings are stored.If false, all resulting columns are of string type. inferSchema: if true, attempts to infer an appropriate type for each resulting DataFrame column, like a boolean, numeric or date type.FAILFAST: throws an exception when it detects corrupted records.DROPMALFORMED: ignores corrupted records.When it encounters a field of the wrong data type, sets the offending field to null.When it encounters a corrupted record, sets all fields to null and puts the malformed string into a new field configured by columnNameOfCorruptRecord.mode: The mode for dealing with corrupt records.nullValue: The value to treat as a null value.excludeAttribute: Whether to exclude attributes in elements.Possible types are StructType, ArrayType, StringType, LongType, DoubleType, BooleanType, TimestampType and NullType, unless you provide a schema. samplingRatio: Sampling ratio for inferring schema (0.0 ~ 1).ssion("local", sparkPackages = c("com.databricks:spark-xml_2.12:"))ĭf.
StructField("title", StringType, nullable = true))) StructField("publish_date", StringType, nullable = true), StructField("price", DoubleType, nullable = true), StructField("genre", StringType, nullable = true), StructField("description", StringType, nullable = true), StructField("author", StringType, nullable = true), StructField("_id", StringType, nullable = true), Val selectedData = df.select("author", "_id") OPTIONS (path "dbfs:/books.xml", rowTag "book")ĬREATE TABLE books (author string, description string, genre string, _id string, price double, publish_date string, title string) Read and write XML data SQL /*Infer schema*/ The example in this section uses the books XML file.
See spark-xml Releases for the latest version of. Databricks Runtime 5.5 LTS and 6.x: com.databricks:spark-xml_2.11:.Databricks Runtime 7.x and above: com.databricks:spark-xml_2.12:.
RequirementsĬreate the spark-xml library as a Maven library.
#DATACROW BOOK FILE IMPORT RECURSIVE HOW TO#
This article describes how to read and write an XML file as an Apache Spark data source.
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