PySpark With MapR

Justin Brandenburg has a tutorial on combining Python and Spark on the MapR platform:

Looking at the first 5 records of the RDD

kddcup_data.take(5)
This output is difficult to read. This is because we are asking PySpark to show us data that is in the RDD format. PySpark has a DataFrame functionality. If the Python version is 2.7 or higher, you can utilize the pandas package. However, pandas doesn’t work on Python versions 2.6, so we use the Spark SQL functionality to create DataFrames for exploration.

The full example is a fairly simple k-means clustering process, which is a great introduction to PySpark.

Related Posts

Anomaly Detection With Kafka Streams

Ajmal Karuthakantakath shows us an application which performs fairly simple anomaly detection using Kafka Streams: The problem is in the banking loan payment domain, where customers have taken a loan and they need to make monthly payments to repay the loan amount. Assume there are millions of customers in the system and all these customers need […]

Read More

Crossing The Streams With Kafka

Himani Arora shows how to join two Kafka streams together: KStream-KStream Join It is a sliding window join, that means, all tuples close to each other with regard to time are joined. Time here is the difference up to size of the window. These joins are always windowed joins because otherwise, the size of the internal state […]

Read More

Categories

August 2016
MTWTFSS
« Jul Sep »
1234567
891011121314
15161718192021
22232425262728
293031