Near real time database queries on samples of data with confidence intervals calculated in parallel.  This meetup will occur on Wednesday Oct 30th at Intel in Santa Clara, Ca.  Register using the link below.  If you blink, you will miss it.  

If you missed the recent AmpCamp 3 event,  you can sign up for #Spark Summit 2013 that will be held at Hotel Nikko in San Francisco, Ca on Monday December 2nd.  You can also register for the additional half day hands on training session on Tuesday December 3rd.  See you at the summit! 

Josh Rosen will be giving a presentation today about using Apache Spark with  #python  via #PySpark.  Look at this Ipython notebook demo http://nbviewer.ipython.org/6384491/00-Setup-IPython-PySpark.ipynb

A  thoughtful Apache Spark streaming example that discusses application requirements and needed computing resources.  This example  demonstrates the flexibility, expressiveness, and testability of Apache Spark.  

Apache Spark 0.8.0 has been released.  This is the first release as an Apache incubator project.  Some of the improvements are monitoring UI, metrics, machine learning library, python improvements, Hadoop Yarn 2.0.5 alpha release support, revamped scheduler, easier deployment, expanded EC2 capabilities, and improved documentation.

Release 0.8 of Apache Spark will be presented on Monday September 30th at Tagged Inc in San Francisco, Ca.  There 65 people signed up with 135 spots still available.  The new release includes MLlib ( machine learning library ),  Python PySpark API enhancements, improved YARN support, new EC2 scripts.   Also, business marketing startup Bizo will present how they use Spark.

Amp Camp 3 Big Data Bootcamp starts today.   Sign up and watch the live streamed presentations about Apache Spark at the link below.

Create a simple standalone Apache Spark job in Scala.  Create a spark context and read in a log file as an RDD of strings.  Then apply transformations and actions to the RDD and print out the results.