c

com.johnsnowlabs.reader

SparkNLPReader

class SparkNLPReader extends Serializable

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  1. SparkNLPReader
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Instance Constructors

  1. new SparkNLPReader(params: Map[String, String] = new java.util.HashMap(), headers: Map[String, String] = new java.util.HashMap())

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  6. def doc(content: Array[Byte]): Seq[HTMLElement]
  7. def doc(docPath: String): DataFrame

    Instantiates class to read Word files.

    Instantiates class to read Word files.

    docPath: this is a path to a directory of Word files or a path to an Word file E.g. "path/word/files"

    Example

    val docsPath = "home/user/word-directory"
val sparkNLPReader = new SparkNLPReader()
val docsDf = sparkNLPReader.email(docsPath)

    Example 2

    You can use SparkNLP for one line of code

    val docsDf = SparkNLP.read.doc(docsPath)
    docsDf.select("doc").show(false)
+----------------------------------------------------------------------------------------------------------------------------------------------------+
|doc                                                                                                                                                 |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
+----------------------------------------------------------------------------------------------------------------------------------------------------+
|[{Table, Header Col 1, {}}, {Table, Header Col 2, {}}, {Table, Lorem ipsum, {}}, {Table, A Link example, {}}, {NarrativeText, Dolor sit amet, {}}]  |
+----------------------------------------------------------------------------------------------------------------------------------------------------+

docsDf.printSchema()
root
 |-- path: string (nullable = true)
 |-- content: binary (nullable = true)
 |-- doc: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- elementType: string (nullable = true)
 |    |    |-- content: string (nullable = true)
 |    |    |-- metadata: map (nullable = true)
 |    |    |    |-- key: string
 |    |    |    |-- value: string (valueContainsNull = true)
  8. def email(content: Array[Byte]): Seq[HTMLElement]
  9. def email(emailPath: String): DataFrame

    Instantiates class to read email files.

    Instantiates class to read email files.

    emailPath: this is a path to a directory of email files or a path to an email file E.g. "path/email/files"

    Example

    val emailsPath = "home/user/emails-directory"
val sparkNLPReader = new SparkNLPReader()
val emailDf = sparkNLPReader.email(emailsPath)

    Example 2

    You can use SparkNLP for one line of code

    val emailDf = SparkNLP.read.email(emailsPath)
    emailDf.select("email").show(false)
+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|email                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|[{Title, Email Text Attachments, {sent_to -> Danilo Burbano <danilo@johnsnowlabs.com>, sent_from -> Danilo Burbano <danilo@johnsnowlabs.com>}}, {NarrativeText, Email  test with two text attachments\r\n\r\nCheers,\r\n\r\n, {sent_to -> Danilo Burbano <danilo@johnsnowlabs.com>, sent_from -> Danilo Burbano <danilo@johnsnowlabs.com>, mimeType -> text/plain}}, {NarrativeText, <html>\r\n<head>\r\n<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">\r\n<style type="text/css" style="display:none;"> P {margin-top:0;margin-bottom:0;} </style>\r\n</head>\r\n<body dir="ltr">\r\n<span style="font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Email&nbsp; test with two text attachments</span>\r\n

\r\n<br>\r\n\r\n

\r\nCheers,\r\n

\r\n<br>\r\n\r\n</body>\r\n</html>\r\n, {sent_to -> Danilo Burbano <danilo@johnsnowlabs.com>, sent_from -> Danilo Burbano <danilo@johnsnowlabs.com>, mimeType -> text/html}}, {Attachment, filename.txt, {sent_to -> Danilo Burbano <danilo@johnsnowlabs.com>, sent_from -> Danilo Burbano <danilo@johnsnowlabs.com>, contentType -> text/plain; name="filename.txt"}}, {NarrativeText, This is the content of the file.\n, {sent_to -> Danilo Burbano <danilo@johnsnowlabs.com>, sent_from -> Danilo Burbano <danilo@johnsnowlabs.com>, mimeType -> text/plain}}, {Attachment, filename2.txt, {sent_to -> Danilo Burbano <danilo@johnsnowlabs.com>, sent_from -> Danilo Burbano <danilo@johnsnowlabs.com>, contentType -> text/plain; name="filename2.txt"}}, {NarrativeText, This is an additional content file.\n, {sent_to -> Danilo Burbano <danilo@johnsnowlabs.com>, sent_from -> Danilo Burbano <danilo@johnsnowlabs.com>, mimeType -> text/plain}}]|
+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

emailDf.printSchema()
root
 |-- path: string (nullable = true)
 |-- content: binary (nullable = true)
 |-- email: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- elementType: string (nullable = true)
 |    |    |-- content: string (nullable = true)
 |    |    |-- metadata: map (nullable = true)
 |    |    |    |-- key: string
 |    |    |    |-- value: string (valueContainsNull = true)
  10. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  11. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  12. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  13. final def getClass(): Class[_]
    Definition Classes
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    Annotations
    @native()
  14. def getOutputColumn: String
  15. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  16. def html(urls: List[String]): DataFrame
  17. def html(urls: Array[String]): DataFrame
  18. def html(htmlPath: String): DataFrame
  19. def htmlToHTMLElement(html: String): Seq[HTMLElement]
  20. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  21. def md(mdPath: String): DataFrame

    Instantiates class to read Markdown (.md) files.

    Instantiates class to read Markdown (.md) files.

    This method loads a Markdown file or directory of .md files and parses the content into structured elements such as headers, narrative text, lists, and code blocks.

    Example

    val mdPath = "home/user/markdown-files"
val sparkNLPReader = new SparkNLPReader()
val mdDf = sparkNLPReader.md(mdPath)

    Example 2

    Use SparkNLP in one line:

    val mdDf = SparkNLP.read.md(mdPath)
    mdDf.select("md").show(false)

+-----------------------------------------------------------------------------------------------------------------------------------+
|md                                                                                                                                 |
+-----------------------------------------------------------------------------------------------------------------------------------+
|[{Title, Introduction, {level -> 1, paragraph -> 0}}, {NarrativeText, This is a Markdown paragraph., {paragraph -> 0}}, ...]        |
+-----------------------------------------------------------------------------------------------------------------------------------+

mdDf.printSchema()
root
 |-- path: string (nullable = true)
 |-- md: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- elementType: string (nullable = true)
 |    |    |-- content: string (nullable = true)
 |    |    |-- metadata: map (nullable = true)
 |    |    |    |-- key: string
 |    |    |    |-- value: string (valueContainsNull = true)
    mdPath

    Path to a single .md file or a directory of Markdown files.

    returns

    A DataFrame with parsed Markdown content as structured HTMLElements.

  22. def mdToHTMLElement(mdContent: String): Seq[HTMLElement]
  23. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  24. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  25. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  26. def pdf(pdfPath: String): DataFrame

    Instantiates class to read PDF files.

    Instantiates class to read PDF files.

    pdfPath: this is a path to a directory of PDF files or a path to an PDF file E.g. "path/pdfs/"

    Example

    val pdfsPath = "home/user/pdfs-directory"
val sparkNLPReader = new SparkNLPReader()
val pdfDf = sparkNLPReader.pdf(pdfsPath)

    Example 2

    You can use SparkNLP for one line of code

    val pdfDf = SparkNLP.read.pdf(pdfsPath)
    pdfDf.show(false)
+--------------------+--------------------+------+--------------------+----------------+---------------+--------------------+---------+-------+
|                path|    modificationTime|length|                text|height_dimension|width_dimension|             content|exception|pagenum|
+--------------------+--------------------+------+--------------------+----------------+---------------+--------------------+---------+-------+
|file:/content/pdf...|2025-01-15 20:48:...| 25803|This is a Title \...|             842|            596|[25 50 44 46 2D 3...|     NULL|      0|
|file:/content/pdf...|2025-01-15 20:48:...|  9487|This is a page.\n...|             841|            595|[25 50 44 46 2D 3...|     NULL|      0|
+--------------------+--------------------+------+--------------------+----------------+---------------+--------------------+---------+-------+

pdf_df.printSchema()
root
 |-- path: string (nullable = true)
 |-- modificationTime: timestamp (nullable = true)
 |-- length: long (nullable = true)
 |-- text: string (nullable = true)
 |-- height_dimension: integer (nullable = true)
 |-- width_dimension: integer (nullable = true)
 |-- content: binary (nullable = true)
 |-- exception: string (nullable = true)
  27. def ppt(content: Array[Byte]): Seq[HTMLElement]
  28. def ppt(docPath: String): DataFrame

    Instantiates class to read PowerPoint files.

    Instantiates class to read PowerPoint files.

    docPath: this is a path to a directory of PowerPoint files or a path to an PowerPoint file E.g. "path/power-point/files"

    Example

    val docsPath = "home/user/power-point-directory"
val sparkNLPReader = new SparkNLPReader()
val pptDf = sparkNLPReader.ppt(docsPath)

    Example 2

    You can use SparkNLP for one line of code

    val pptDf = SparkNLP.read.ppt(docsPath)
    xlsDf.select("ppt").show(false)
+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|ppt                                                                                                                                                                                                                                                                                                                      |
+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|[{Title, Adding a Bullet Slide, {}}, {ListItem, • Find the bullet slide layout, {}}, {ListItem, – Use _TextFrame.text for first bullet, {}}, {ListItem, • Use _TextFrame.add_paragraph() for subsequent bullets, {}}, {NarrativeText, Here is a lot of text!, {}}, {NarrativeText, Here is some text in a text box!, {}}]|
+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

pptDf.printSchema()
root
 |-- path: string (nullable = true)
 |-- content: binary (nullable = true)
 |-- ppt: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- elementType: string (nullable = true)
 |    |    |-- content: string (nullable = true)
 |    |    |-- metadata: map (nullable = true)
 |    |    |    |-- key: string
 |    |    |    |-- value: string (valueContainsNull = true)
  29. def setOutputColumn(value: String): Unit
  30. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  31. def toString(): String
    Definition Classes
    AnyRef → Any
  32. def txt(filePath: String): DataFrame

    Instantiates class to read txt files.

    Instantiates class to read txt files.

    filePath: this is a path to a directory of TXT files or a path to an TXT file E.g. "path/txt/files"

    Example

    val filePath = "home/user/txt/files"
val sparkNLPReader = new SparkNLPReader()
val txtDf = sparkNLPReader.txt(filePath)

    Example 2

    You can use SparkNLP for one line of code

    val txtDf = SparkNLP.read.txt(filePath)
    txtDf.select("txt").show(false)
+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|txt                                                                                                                                                                                                                                                                                                                                                                                                                                        |
+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|[{Title, BIG DATA ANALYTICS, {paragraph -> 0}}, {NarrativeText, Apache Spark is a fast and general-purpose cluster computing system.\nIt provides high-level APIs in Java, Scala, Python, and R., {paragraph -> 0}}, {Title, MACHINE LEARNING, {paragraph -> 1}}, {NarrativeText, Spark's MLlib provides scalable machine learning algorithms.\nIt includes tools for classification, regression, clustering, and more., {paragraph -> 1}}]|
+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

emailDf.printSchema()
root
 |-- path: string (nullable = true)
 |-- content: binary (nullable = true)
 |-- txt: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- elementType: string (nullable = true)
 |    |    |-- content: string (nullable = true)
 |    |    |-- metadata: map (nullable = true)
 |    |    |    |-- key: string
 |    |    |    |-- value: string (valueContainsNull = true)
  33. def txtContent(content: String): DataFrame
  34. def txtToHTMLElement(text: String): Seq[HTMLElement]
  35. def urlToHTMLElement(url: String): Seq[HTMLElement]
  36. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  37. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  38. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  39. def xls(content: Array[Byte]): Seq[HTMLElement]
  40. def xls(docPath: String): DataFrame

    Instantiates class to read Excel files.

    Instantiates class to read Excel files.

    docPath: this is a path to a directory of Excel files or a path to an Excel file E.g. "path/excel/files"

    Example

    val docsPath = "home/user/excel-directory"
val sparkNLPReader = new SparkNLPReader()
val xlsDf = sparkNLPReader.xls(docsPath)

    Example 2

    You can use SparkNLP for one line of code

    val xlsDf = SparkNLP.read.xls(docsPath)
    xlsDf.select("xls").show(false)
+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|xls                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|[{Title, Financial performance, {SheetName -> Index}}, {Title, Topic\tPeriod\t\t\tPage, {SheetName -> Index}}, {NarrativeText, Quarterly revenue\tNine quarters to 30 June 2023\t\t\t1.0, {SheetName -> Index}}, {NarrativeText, Group financial performance\tFY 22\tFY 23\t\t2.0, {SheetName -> Index}}, {NarrativeText, Segmental results\tFY 22\tFY 23\t\t3.0, {SheetName -> Index}}, {NarrativeText, Segmental analysis\tFY 22\tFY 23\t\t4.0, {SheetName -> Index}}, {NarrativeText, Cash flow\tFY 22\tFY 23\t\t5.0, {SheetName -> Index}}, {Title, Operational metrics, {SheetName -> Index}}, {Title, Topic\tPeriod\t\t\tPage, {SheetName -> Index}}, {NarrativeText, Mobile customers\tNine quarters to 30 June 2023\t\t\t6.0, {SheetName -> Index}}, {NarrativeText, Fixed broadband customers\tNine quarters to 30 June 2023\t\t\t7.0, {SheetName -> Index}}, {NarrativeText, Marketable homes passed\tNine quarters to 30 June 2023\t\t\t8.0, {SheetName -> Index}}, {NarrativeText, TV customers\tNine quarters to 30 June 2023\t\t\t9.0, {SheetName -> Index}}, {NarrativeText, Converged customers\tNine quarters to 30 June 2023\t\t\t10.0, {SheetName -> Index}}, {NarrativeText, Mobile churn\tNine quarters to 30 June 2023\t\t\t11.0, {SheetName -> Index}}, {NarrativeText, Mobile data usage\tNine quarters to 30 June 2023\t\t\t12.0, {SheetName -> Index}}, {NarrativeText, Mobile ARPU\tNine quarters to 30 June 2023\t\t\t13.0, {SheetName -> Index}}, {Title, Other, {SheetName -> Index}}, {Title, Topic\tPeriod\t\t\tPage, {SheetName -> Index}}, {NarrativeText, Average foreign exchange rates\tNine quarters to 30 June 2023\t\t\t14.0, {SheetName -> Index}}, {NarrativeText, Guidance rates\tFY 23/24\t\t\t14.0, {SheetName -> Index}}]|
+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

xlsDf.printSchema()
root
 |-- path: string (nullable = true)
 |-- content: binary (nullable = true)
 |-- xls: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- elementType: string (nullable = true)
 |    |    |-- content: string (nullable = true)
 |    |    |-- metadata: map (nullable = true)
 |    |    |    |-- key: string
 |    |    |    |-- value: string (valueContainsNull = true)
  41. def xml(xmlPath: String): DataFrame

    Instantiates class to read XML files.

    Instantiates class to read XML files.

    xmlPath: this is a path to a directory of XML files or a path to an XML file. E.g., "path/xml/files"

    Example

    val xmlPath = "home/user/xml-directory"
val sparkNLPReader = new SparkNLPReader()
val xmlDf = sparkNLPReader.xml(xmlPath)

    Example 2

    You can use SparkNLP for one line of code

    val xmlDf = SparkNLP.read.xml(xmlPath)
    xmlDf.select("xml").show(false)
+------------------------------------------------------------------------------------------------------------------------+
|xml                                                                                                                    |
+------------------------------------------------------------------------------------------------------------------------+
|[{Title, John Smith, {elementId -> ..., tag -> title}}, {UncategorizedText, Some content..., {elementId -> ...}}]     |
+------------------------------------------------------------------------------------------------------------------------+

xmlDf.printSchema()
root
 |-- path: string (nullable = true)
 |-- xml: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- elementType: string (nullable = true)
 |    |    |-- content: string (nullable = true)
 |    |    |-- metadata: map (nullable = true)
 |    |    |    |-- key: string
 |    |    |    |-- value: string (valueContainsNull = true)
    xmlPath

    Path to the XML file or directory

    returns

    A DataFrame with parsed XML as structured elements

  42. def xmlToHTMLElement(xml: String): Seq[HTMLElement]

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