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XML

Load data from an .xml file into Visual Notebooks.

Configuration

FieldDescription
Name default=name of the first uploaded fileA user-specified node name displayed in the workspace
File RequiredThe file or files to upload
Upload data from an .xml file. If uploading multiple files, make sure all files have the same structure and type of data. Files are stored in a scalable cloud environment with stringent security measures. The total size of all uploaded files must not exceed 50 GB.
Schema inference mode default=Auto-detect schema - drop rows containing bad valuesData type inference options
Select the "Auto-detect schema - drop rows containing bad values" option to infer the data type (string, integer, decimal, Boolean, etc.) used in each column. Rows with different data types or empty values are not uploaded to the workspace. Select the "Read as strings - no schema inference" option to read all columns as strings and upload all values.
Sampling ratio to inference schema (%) default=20Percentage of data used to infer schema
Set this slider to any percentage. Visual Notebooks examines the percentage of data specified and uses it to determine data types, tags, and timestamps.
Define tags default=Auto-detect rowTag and rootTagTag inference options
Select the "Auto-detect rowTag and rootTag" option to infer the rowTag and rootTag used in the uploaded file. The rootTag brackets the entire file and the rowTag brackets each row. If Visual Notebooks does not correctly infer the tags, select the "Custom define rowTag and rootTag" option to manually enter the rowTag and rootTag used in the uploaded file.
Timestamp format option default=Autodetect timestamp formatTimestamp inference options
Select the "Autodetect timestamp format" option to infer timestamp formatting. Visual Notebooks examines the percentage of data specified in the "Sampling ratio to inference schema" field and compares those values to a list of known timestamp formats. Select the "Specify timestamp format" option to manually enter the exact timestamp format used in the uploaded file.

Node Inputs/Outputs

InputNone
OutputVisual Notebooks returns a table, called a dataframe, that contains all uploaded data. Columns are labeled and include a symbol that specifies the data type of that column.

Example dataframe output

Figure 1: Example dataframe output

Examples

  • Drag and drop the .xml file that you want to upload into the outlined space,
    or use the "Browse" button to select files from your computer.
    • The file shown below is used in this example. Notice that there are ten
      rows of data.
    • The rowTag is and the rootTag is. Visual Notebooks infers these
      without user input.

Example source data file

Figure 2: Example source data file

  • Upload this file then select "Run" to create a dataframe with the default
    settings.
    • Notice that the columns include an icon that indicates the data type.
    • By default, Visual Notebooks drops rows with missing values or mismatched data
      types. Since there are only eight rows in the dataframe, two rows have
      been dropped.

Example dataframe with default settings

Figure 3: Example dataframe with default settings

  • To preserve all rows, select the "Read as strings (no schema inference)"
    option.
    • Notice that all ten rows are imported into the dataframe, including the
      two rows with mismatched data types.
    • The "A" icon next to each column label indicates that all columns are
      stored as strings.

Example dataframe with all data imported as strings

Figure 4: Example dataframe with all data imported as strings

  • If you want to convert a column to a date or timestamp type, reference the Spark SQL
    guide     for an
    explanation of the available datetime symbols. The table below shows example timestamp
    formats.

Example timestamp formats

Figure 5: Example timestamp formats

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