Hadoop MapReduce startup task

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about 7 years ago

$30-250 AUD

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Given a text file, compute the average length of words starting with each letter. This means that for every letter, you need to compute: the total length of all words that start with that letter divided by the total number of words that start with that letter. • Ignore the letter case, i.e., consider all words as lower case. • Ignore terms starting with non-alphabetical characters, i.e., only consider terms starting with “a” to “z”. • The length of the term is obtained by the length() function of String. E.g., the length of “text234sdf” is 10. • Use the tokenizer give in Lab 3 to split the documents into terms. StringTokenizer itr = new StringTokenizer([login to view URL](), " *$&#/\t\n\f\"'\\,.:;?![](){}<>~-_"); • You do not need to configure the numbers of mappers and reducers. Default values will be used.

Hadoop

Map Reduce

Project ID: 13584402

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Remote project

Active 7 yrs ago

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3 freelancers are bidding on average $233 AUD for this job

@eaglepoint

Hi I am a big data engineer with 2 years of full industry experience. I have practical experience of Hadoop and its various applications in its ecosystem. I can do this job for you. Looking forward for your response Thanks

$200 AUD in 3 days

5.0

(8 reviews)

4.7

@farrukhcheema23

Hi, I am a Big Data Consultant with over 4 years of experience. I have read your request and interested to work for you as I am expert of Hadoop, MapReduce, Spark, Scala and can write a MapReduce program to do this task for you very professionally. I have wrote MapReduce code many times before in hadoop environment and can show you few examples. Please lets have a chat and discuss it in little more details. I am available to start working now and you will have it done very fast. I am waiting for your response. Please give me a chance to do it for you. Thank you

$250 AUD in 3 days

5.0

(2 reviews)

2.6

@souvikghosh

Hi there, I have been working in the Hadoop framework for over 3 years now. Hadoop has changed a lot from what it was in the initial years. From a mere low cost solution for large dataset storing via HDFS and analysis via MapReduce to a myriad of applications that is constantly evolving. The most used tools in the Hadoop ecosystem now a days are Spark (in memory proccessor that is slated to be the replacement of Mapreduce), Hive (the default database for the hadoop ecosystem tools), Impala, R, pig, Hbase etc. But the actual set of big data tools depends on the exact requirement of the project and the expected outcome. I am currently working in a few big data projects in my company and can surely help you to in your project as a Big Data Architect. In fact in the current project in my company, I am doing the exact same thing i.e. We are calculating Economic Capital i.e. Risk Capital of Insurance firms and using diffrent models for the calcualtion. The Sprak engine reads all the data from the Hive table, then does the Model calculation in its in memory spark engine and the results are written in another Hive table in the form of an OLAP Cube. Our visualization tool (Tableau) reads from this Hive Cube and dispalys the data to the end business user. We are also using Oozie to schedule workflows. Let me know if you have any questions. Thanks, Souvik

$250 AUD in 2 days