Github user marmbrus commented on the pull request:
https://github.com/apache/spark/pull/4434#issuecomment-103973399
We should move this discussion off of github and onto the mailing list, but
creating a dataframe is not expensive. The following seems easier to me than
the example presented here.
```python
from pyspark.sql import Row
df = sc.parallelize([Row(name="Michael", age=30)]).toDF()
df.save("/home/michael/people.avro", "com.databricks.spark.avro")
df.save("/home/michael/people.json", "json")
sqlContext.load("/home/michael/people", "com.databricks.spark.avro")
Out[6]: DataFrame[age: bigint, name: string]
```
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