Databricks Community

@dan11 We don't support number in Spark SQL. Try using int, double, float, and your query should be fine. To run SQL in a notebook, just prepend any cell with %sql. %sql select cast(myage as double) as my_integer_age from ages;

I'm facing the same problem, does anybody know how to connect Spark in Ipython notebook? The issue I created, https://github.com/jupyter/notebook/issues/743

Use take()

Analyze is not needed with parquet tables that use the databricks parquet package. That is the default now when you use .saveAsTable(), but if you use a different output format - it's possible that analyze may not work yet.

Looks like the following property is pretty high, which consumes a lot of memory on your executors when you cache the dataset. "spark.storage.memoryFraction:0.9" This could likely be solved by changing the configuration. Take a look at the upstream...

There is no hardcoded limit we just call panda.fromRecords with a collection of fields to instantiate a new Panda Dataframe. The only limit is memory. See http://stackoverflow.com/questions/15455722/pandas-is-there-a-max-size-max-no-of-columns-max-r...

Sorted DataIf your data is sorted using either sort() or ORDER BY, these operations will be deterministic and return either the 1st element using first()/head() or the top-n using head(n)/take(n).show()/show(n) return Unit (void) and will print up to...

How do you set this size ?

Hover between the cells in the side-to-side middle and you will see a + sign appear. This is how you can insert cells into the top-to-bottom middle of a notebook. You can also move cells by hovering in the upper left of each cell. A cross-hairs will...