Advice on how to design and build your Apache Spark application for testability
Map Reduce can be used in jobs such as pattern-based searching, web access log stats, document clustering, web link-graph reversal, inverted index construction, term-vector per host, statistical machine translation and machine learning. Text indexing, search, and tokenization can also be accomplished with the Map Reduce program.
Map Reduce can also be used in different environments such as desktop grids, dynamic cloud environments, volunteer computing environments and mobile environments. Those who want to apply for Map Reduce jobs can educate themselves with the many tutorials available in the internet. Focus should be put on studying the input reader, map function, partition function, comparison function, reduce function and output writer components of the program. Hire Map Reduce Developers
Hi, i have a big data project for my startup that I would love help with. Need help with optimizing my Cloudera 5.11 infrastructure as well as optimizing the performance of some scrapers for my wine analytics application. Also have sentiment analysis training that I need help with (my system does it natively using spark but needs to be trained still). Please be sure to list your experience with Cloudera in your application as well as any other strong skills you have that aren't listed in your profile.
Video Training on Big Data Hadoop. It would be screen recording and voice over. The recording will be approx 8 hrs Must cover Hadoop, MapReduce, HDFS, Spark, Pig, Hive, HBase, MongoDB, Cassandra, Flume
I need someone who is expert on map modules to develop indoor wayfinding module where back end will manage the operations of building the 3d/2D map and end users can use it in their devices to locate locations inside the building.
I have an application in which user selects a folder from hdfs, and the application writes the results in hdfs/output/directory. so we need to write code in java for checking permissions of output directory before writing the results in hdfs/output/directory.
We have an app that collects data from a users body. Some data has 10 readings per second while other have only one reading every 10 or 30 seconds. There are approximately 15 values being measured during a test. Each test can last from 10 seconds to hours of data being collected. There is also data about each user such as their weight, height, body type, medical conditions etc.. Additionally each session will have information about their state such as activity level, stress level, energy level. The information will be sent from our app to our server. You need to also create an api or have one created to receive information from the phone and send to the phone app if necessary as well as for their login and password. We are expecting a lot of users so we want to start with an architecture designed for high volume. Additionally we want to analyze all of the data in many ways in individual accounts as well as across all accounts to find useful patterns. The main part of this project is to: 1) Create the user interface 2) Allow people to see a list of each of their sessions 3) Click within each session to explore the data. There will be about 6 graphs and other data related to their session. I'm thinking of something like Hadoop or Cassandra will be the best but I'm open to suggestions. Something that will scale with us as our userbase and data increases.
Job Type- Contract Duration- 2 to 4 months Location- Gurgaon Positions- 2 Please share only immediate joiners: JD: • 4-5 years’ experience in Big data technologies like Map Reduce, Kafka, Hadoop, PIG, Oozie • Experience in Hadoop cluster migration to AWS (Amazon Web Services) • Should have Parquet and ORC knowledge • Should have knowledge on Hadoop cluster encryption • Should have knowledge on Hadoop Security architecture • Good to have knowledge on Disaster recovery Kindly connect on 8750545849