title: Redshift and ultra wide tables
body: <p>In attempt to handle custom fields for specific objects in multi-tenant dimensional DW I created ultra wide denormalized dimension table (hundreds of columns, hard coded limit of column) that Redshift is not liking too much ;). </p>
  
  <blockquote>
    <p>user1|attr1|attr2...attr500</p>
  </blockquote>
  
  <p>Even innocent update query on single column on handful of records takes approximately 20 seconds. (Which is kind of surprising as I would guess it shouldn't be such a problem on columnar database.) </p>
  
  <p>Any pointer how to modify design for better reporting from normalized source table (one user has multiple different attributes, one attribute is one line) to denormalized (one row per user with generic columns, different for each of the tenants)? </p>
  
  <p>Or anyone tried to perform transposing (pivoting) of normalized records into denormalized view (table) in Redshift? I am worried about performance.</p>