The split function takes a regular expression as pattern so you can write something which works for you.įinal note the limit parameter is supported since spark >= 3. Note that your real data might be more complex or structured differently and this solution might not work.
Splitted = F.split(F.col('value'), ',', limit=cols_to_split)ĭf.select(.alias(f'col') for i in range(cols_to_split)]).show() From the resulting array we select the columns we want. Here we read the csv as a text file and split it up to the 4th comma. For your example this can can be done as below. If that is not an option can split the file yourself after reading it. The best option would be to ask your source to deliver a better formatted csv file (or use a different separator) It was derived from JavaScript, but as of 2017 many programming languages include code to generate and parse JSON-format data.The problem here is that your csv separator is also used in the json column without it being escaped or the column being quoted. Csvjson helps you quickly convert popular data formats to the format you need. JSON is a language-independent data format. The easy, confidential online data converter. Traditionally developers will be flattening JSON to CSV. JSON is a very common data format used for asynchronous browser-server communication, including as a replacement for XML in some AJAX-style systems. Parsing CSV files easily like a Pro is very easy with CSVKit. CSV implementations may not handle such field data, or they may use quotation marks to surround the field. Just paste your CSV in the input field below and it will automatically get converted to JSON.
The basic idea of separating fields with a comma is clear, but that idea gets complicated when the field data may also contain commas or even embedded line-breaks. In computing, JavaScript Object Notation or JSON is an open-standard file format that uses human-readable text to transmit data objects consisting of attribute-value pairs and array data types (or any other serializable value). The use of the comma as a field separator is the source of the name for this file format. Each record consists of one or more fields, separated by commas. Read this data with spark code to have output in this format in the dataframe. In computing, a comma-separated values (CSV) file stores tabular data (numbers and text) in plain text. Spark csv reader - malformed json inside csv last column.
0 kommentar(er)
