title: Loading a CSV file from Blob Storage Container using PySpark
body: <p>I am unable to load a CSV file directly from Azure Blob Storage into a RDD by using PySpark in a Jupyter Notebook.</p>
  
  <p>I have read through just about all of the other answers to similar problems but I haven't found specific instructions for what I am trying to do. I know I could also load the data into the Notebook by using Pandas, but then I would need to convert the Panda DF into an RDD afterwards.</p>
  
  <p>My ideal solution would look something like this, but this specific code give me the error that it can't infer a schema for CSV.</p>
  
  <p><code>#Load Data
  source = &lt;Blob SAS URL&gt;
  elog = spark.read.format("csv").option("inferSchema", "true").option("url",source).load()
  </code></p>
  
  <p>I have also taken a look at this answer: <a href="https://stackoverflow.com/questions/47871611/reading-a-csv-file-from-azure-blob-storage-with-pyspark">reading a csv file from azure blob storage with PySpark</a>
  but I am having trouble defining the correct path.</p>
  
  <p>Thank you very much for your help!</p>