title: Move data from PostgreSQL to AWS S3 and analyze with RedShift Spectrum
body: <p>I have a big amount of PostgreSQL tables with different schemas and the massive amount of data inside them.</p>
  
  <p>I'm unable to do the data analytics right now because the data amount is quite large - a few TB of data and PostgreSQL is not able to process queries in a reasonable amount of time.</p>
  
  <p>I'm thinking about the following approach - I'll process all of my PostgreSQL tables with Apache Spark, load the DataFrames and store them as the Parquet files in AWS S3. Then I'll use RedShift Spectrum in order to query the information stored inside of these PARQUET files.</p>
  
  <p>First of all, I'd like to ask - will this solution work at all?</p>
  
  <p>And the second - will RedShift Spectrum be able to automatically create EXTERNAL tables from these Parquet files without additional schema specification(even when the original PostgreSQL tables contain the unsupported data types by AWS RedShift)?</p>