Enable the use of R as a query language for big data: Big R hides many of the complexities pertaining to the underlying Hadoop / MapReduce framework. Using classes such as bigr.frame, bigr.vector and bigr.list, a user is presented with an API that is heavily inspired by Rs foundational API on data.frames, vectors and frames.
Enable the pushdown of R functions such that they run right on the data: Via mechanisms such as groupApply, rowApply and tableApply, user-written functions composed in R can be shipped to the cluster. BigInsights transparently parallelizes execution of these functions and provides consolidated results back to the user. Almost any R code, including most packages available on open-source repositories such as CRAN (Comprehensive R Archive Network), can be run using this mechanism.
Question : You are working as a BigData Analytics , and you need to integrate IBM SPSS Modeler to use big data as a source for predictive modeling. Which of the following will help to do this
Correct Answer : Get Lastest Questions and Answer : Explanation: IBM SPSS Analytic Server enables IBM SPSS Modeler to use big data as a source for predictive modeling. Together they can provide an integrated predictive analytics platform using data from Hadoop distributions and Spark applications. Move analytics to the data to optimize performance. Access data from Hadoop and combine it with RDBMS to expand data access. Apply real-time processing and machine learning to conduct deeper analysis and accelerate resultsand reduce coding and simplify algorithm development. The combination also provides defined interfaces that simplify big data analysis for both analysts and business users.
1. Fair Scheduler allows assigning guaranteed minimum shares to queues 2. queue does not need its full guaranteed share, the excess will not be splitted between other running apps. 3. it is also possible to limit the number of running apps per user and per queue 4. 1 and 3 5. 1,2 and 3
1. Open a remote terminal to the node running the ApplicationMaster and kill the JVM.
2. yarn application -kill "application_id" 3. Use CTRL-C from the terminal where the MapReduce job was started. 4. hadoop datanode -rollback 5. rmadmin -refreshQueues