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    939 mapreduce trabajados encontrados, precios en USD
    esquema maestro-trabajador 1 día left
    VERIFICADO

    consiste en desarrollar un esquema maestro-trabajador, como el esquema de procesamiento mas habitual en los entornos de computacion distribuida, parecido a modelos tan famosos como mapReduce

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    Ingeniero de Datos Finalizado left

    Buscamos perfil profesional para desempeñarse como Ingeniero de Datos modalidad Freelance para proyecto en el rubro Minería. Excluyente experiencia de sobre 2 años como Desarrollador: Big Data Azure, Hadoop, MapReduce, Spark, Hive, Synapse Analytic, Python (o SCADA)

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    Me gustaría un curso de varias clases (cada clase un vídeo diferente) para aprender a utilizar Hadoop y MapReduce, al principio desde cero, e incrementando el nivel con cada clase, empezando con lo básico hasta los niveles más avanzados, para aprender y entender completamente Hadoop y MapReduce para Big Data. El mínimo total de duración sumando todas las clases que sea de 30 minutos. Importantísimo, idioma ESPAÑOL, sino no me sirve

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    Big Data Architect Finalizado left

    Se trata de un proyecto generación de estrategia de Big Data para Business Analytics , las fases que queremos cubrir son las de revisión y auditoría de las fuentes de datos (estructurados - no estructurados) y el apoyo téc...sistemas operativos y redes. • Arquitectura de centro de procesos de datos y creación de Data Lakes (Cloudera,HortonWorks,MapR) • Familiarización con entornos de procesamientos modernos a escala masiva (Big Data) y/o en tiempo real: Hadoop/Mapreduce, HBase Scala/Spark, dataflow, Storm, Flume. • Conocimientos del entorno Salesforce •...

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    ...programación como Java, Scala o Python. Es imprescindible saber para qué y por qué se usan las tecnologías para poder modelar la mejor arquitectura posible para un determinado problema concreto de negocio. Buscamos: Titulados en Informática, Matemáticas, Estadística, etc Requisitos mínimos Experiencia con Git Lenguajes de programación: Java, Python, Scala, R... Experiencia en desarrollo de procesos MapReduce en Hadoop, Spark o Flink Manipulación de datos en diferentes DB Nosql como Cassandra, Mongo o HBase Requisitos deseados Experiencia en desarrollo de procesos Real Time con Storm, Spark o Flink Experiencia o conocimiento de las herramientas del ecosistema Hadoop Librerías y/o tecnologí...

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    ...Profesional graduado en Informática, Economía, Actuario, Ciencias Exactas, oespecialistas en Data mining o Big Data.- Excelentes habilidades de comunicación, proactividad, capacidad de organización yplanificación.- Conocimientos de SQL.- Habilidad para crear modelos analíticos complejos y algoritmos.- Conocimientos de programación sobre herramientas y aplicaciones de Big Data (Hadoop/HDFS, Spark, MapReduce, Hive, R y Python)-Capacidad de abstracción y creatividad para resolver problemas complejos- Buena disposición tanto para el trabajo individual como para el trabajo en de trabajo: Saavedra, Capital :- Ambiente de trabajo desafiante y exigente pero a su vez alegre y divertido, para que hagas lo que más te gus...

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    BluePatagon empresa líder en tecnologías de Business Intelligence & Business Analytics, está en búsqueda de Especialista en Big Data (Hadoop - Hortonworks), para importante cliente de CABA. Experiencia: mínima de 1 año en tecnologías Hadoop: Experiencia en desarrollo de aplicaciones (MapReduce + HDFS). Big Data: Familiaridad con el ecosistema (Hive, Pig, HBase, etc). y conceptos de escalabilidad, análisis en tiempo real, procesamiento de datos distribuidos. Linux: Uso Avanzado (manejo de servicios de SO, administración, shell scripting, seguridad) Programacion: POO (Java preferentemente, Python) Base de datos: RDBMS (Oracle, MySQL, PostgreSQL), NoSQL (HBase, Cassandra) Data Exchange y configuraci&oacu...

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    El backend estaría compuesto por el lenguaje de programación Python, aunque también se programaría en Javascript haciendo uso de tecnologías como NodeJS.  La base de datos sería por un lado relacional PosgreSQL y por otro lado también utilizaríamo...relacional tipo MongoDB Para la plataforma en sí haríamos uso de tecnologías de frontend como AngularJS, HTML5, CSS3 etc. Básicamente es: lenguaje de programación PYTHON en el backend (en los servidores con los procesos de análisis de información) y JAVASCRIPT con el framework de AngularJS en la parte de cliente. Para el análisis de datos se utilizarán tecnologías usadas en Big Data como Hadoop, MapReduce, ...

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    ...experiencia en NoSQL /HBASE, Cassandra o similares, Neo4j). Voluntad de aprender e implementar nuevas tecnologías BigData, según sea necesario. Iniciativa y capacidad de trabajar de manera independiente y en equipo. Experiencia con Sotrm en soluciones real time analytics. Experiencia en procesamiento paralelo (MPI, OpenMP) como ventaja competitiva para el puesto. Experto en comprensión en Hadoop HDFS y MapReduce. Pensamiento creativo (Out of the box) Capacidad en gestión de equipos <em>InnoQuant acaba de ser seleccionado como uno de los 10 startups tecnológicas más prometedoras en España.  Somos un equipo experimentado de profesionales de TI que trabajan en tiempo real plataforma de análisis de grandes datos del ...

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    looking for java developer Final left
    VERIFICADO

    I am looking for a java developer who is -familiar with hadoop architecture and mapreduce scheduling -familiar with modifying the open source packages

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    Big data project Finalizado left

    ...7910/DVN/HG7NV7 4. Design, implement and run an Oozie workflow to find out a. the 3 airlines with the highest and lowest probability, respectively, of being on schedule; b. the 3 airports with the longest and shortest average taxi time per flight (both in and out), respectively; and c. the most common reason for flight cancellations. • Requirements: 1. Your workflow must contain at least three MapReduce jobs that run in fully distributed mode. 2. Run your workflow to analyze the entire data set (total 22 years from 1987 to 2008) at one time on two VMs first and then gradually increase the system scale to the maximum allowed number of VMs for at least 5 increment steps, and measure each corresponding workflow execution time. 3. Run your workflow to analyze the data in a prog...

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    data scientist neaded Finalizado left

    ...7910/DVN/HG7NV7 4. Design, implement and run an Oozie workflow to find out a. the 3 airlines with the highest and lowest probability, respectively, of being on schedule; b. the 3 airports with the longest and shortest average taxi time per flight (both in and out), respectively; and c. the most common reason for flight cancellations. • Requirements: 1. Your workflow must contain at least three MapReduce jobs that run in fully distributed mode. 2. Run your workflow to analyze the entire data set (total 22 years from 1987 to 2008) at one time on two VMs first and then gradually increase the system scale to the maximum allowed number of VMs for at least 5 increment steps, and measure each corresponding workflow execution time. 3. Run your workflow to analyze the data in a prog...

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    ...7910/DVN/HG7NV7 4. Design, implement and run an Oozie workflow to find out a. the 3 airlines with the highest and lowest probability, respectively, of being on schedule; b. the 3 airports with the longest and shortest average taxi time per flight (both in and out), respectively; and c. the most common reason for flight cancellations. • Requirements: 1. Your workflow must contain at least three MapReduce jobs that run in fully distributed mode. 2. Run your workflow to analyze the entire data set (total 22 years from 1987 to 2008) at one time on two VMs first and then gradually increase the system scale to the maximum allowed number of VMs for at least 5 increment steps, and measure each corresponding workflow execution time. 3. Run your workflow to analyze the data in a prog...

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    data project Finalizado left

    ...7910/DVN/HG7NV7 4. Design, implement and run an Oozie workflow to find out a. the 3 airlines with the highest and lowest probability, respectively, of being on schedule; b. the 3 airports with the longest and shortest average taxi time per flight (both in and out), respectively; and c. the most common reason for flight cancellations. • Requirements: 1. Your workflow must contain at least three MapReduce jobs that run in fully distributed mode. 2. Run your workflow to analyze the entire data set (total 22 years from 1987 to 2008) at one time on two VMs first and then gradually increase the system scale to the maximum allowed number of VMs for at least 5 increment steps, and measure each corresponding workflow execution time. 3. Run your workflow to analyze the data in a prog...

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    data progect Finalizado left

    ...7910/DVN/HG7NV7 4. Design, implement and run an Oozie workflow to find out a. the 3 airlines with the highest and lowest probability, respectively, of being on schedule; b. the 3 airports with the longest and shortest average taxi time per flight (both in and out), respectively; and c. the most common reason for flight cancellations. • Requirements: 1. Your workflow must contain at least three MapReduce jobs that run in fully distributed mode. 2. Run your workflow to analyze the entire data set (total 22 years from 1987 to 2008) at one time on two VMs first and then gradually increase the system scale to the maximum allowed number of VMs for at least 5 increment steps, and measure each corresponding workflow execution time. 3. Run your workflow to analyze the data in a prog...

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    Familiarity with Hadoop ecosystem and its components: obviously, a must! Ability to write reliable, manageable, and high-performance code Expertise knowledge of Hadoop HDFS, Hive, Pig, Flume and Sqoop. Working experience in HQL Experience of writing Pig Latin and MapReduce jobs Good knowledge of the concepts of Hadoop. Analytical and problem-solving skills; the implementation of these skills in Big Data domain Understanding of data loading tools such as Flume, Sqoop etc Good knowledge of database principles, practices, structures, and theories

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    Using ansible, harvest twitter data with geo coordinates using twitter API and put into a couchDB. The CouchDB setup may be a single node or based on a cluster setup. The cloud based solution should use 4 VMs with 8 virtual CPUs and 500Gb of volume storage. The data is then combined with other useful geographic data to produce some visualization summary results using MapReduce.

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    Write a MapReduce program to analyze the income data extracted from the 1990 U.S. Census data and determine whether most Americans make more than $50,000 or $50,000 or less a year in 1990. Provide the number of people who made more than $50,000 and the number of people who made $50,000 or less. Download data from http://archive.ics.uci.edu/ml/datasets/Census+Income

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    Urgente
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    1 Explain the concept of Big Data and its importance in a modern economy 2 Explain the core architecture and algorithms underpinning big data processing 3 Analyse and visualize large data sets using a range of statistical and big data technologies 4 Critically evaluate, select and employ appropriate tools and technologies for the development of big data applications

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    Sellado Acuerdo de Confidencialidad
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    Big Data task with the use of python and hadoop using mapreduce techniques

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    big data management Finalizado left

    Hadoop, Implementation of MapReduce application

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    Parsing, Cleaning, and Profiling of the attached file by removing hashtags, emoticons, or any redundant data which is not useful for analysis. And MapReduce output will be on HDFS like the image attached named "Output" but should be clean. Tasks: Dataset: Programming: MapReduce with Java Data profiling: Write MapReduce java code to characterize (profile) the data in each column. Data cleaning: Cleaning and Profiling the tweets by removing hashtags, emoticons, or any redundant data which is not useful for analysis. Write MapReduce java code to ETL (extract, transform, load) data source. Drop some unimportant columns, Normalize data in a column, and Detect badly formatted rows.

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    ...con l’architettura utilizzata in tutta l’azienda. Competenze richieste - Laurea in Informatica, Information Technology o equivalente esperienza tecnica. - Almeno 3 anni di esperienza professionale. - Profonda conoscenza ed esperienza in statistica. - Previa esperienza in programmazione, preferibilmente in Python, Kafka o Java e volontà di apprende nuovi linguaggi. - Competenze su Hadoop v2, MapReduce, HDFS. - Buona conoscenza dei Big Data querying tools. - Esperienza con Spark. -Esperienza nel processare grandi quantità di dati, sia strutturati che non, inclusa l’integrazione di dati che provengono da fonti diverse. - Esperienza con NoSQL databases, come Cassandra o MongoDB. - Esperienza con vari sistemi di messagistica, come Kafka o RabbitMQ Du...

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    Hadoop - Mapreduce Finalizado left

    I need some help with a small task completing some beginning steps in Hadoop with python. Come to the chat and I can explain more. It will not take long, the only thing you need is virtualbox and some som python & Hadoop knowledge.

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    Cleaning and Profiling the tweets by removing hashtags, emoticons, or any redundant data which is not useful for analysis. Organize the use... or any redundant data which is not useful for analysis. Organize the user_location column in a common standard format. Dataset has been attached. Or you can get it from the link below: Tasks: Data profiling: Write MapReduce java code to characterize (profile) the data in each column. Data cleaning: Cleaning and Profiling the tweets by removing hashtags, emoticons, or any redundant data which is not useful for analysis. Write MapReduce java code to ETL (extract, transform, load) data source. Drop some unimportant columns, Normalize data in a column, and Detect badly formatted rows.

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    Detailed summary must contain the main theme of the paper, the approach considered for the work, limitation, current trend in this area and your own judgement on the weakness of the paper. The article is attached separately with this assignment. Summary must include the following: - Understand the contribution of the paper - Understand the technologies - Analyse the current Trend with respect to each paper - Identify the drawback of the paper - Any alternative improvement - Follow IEEE reference style Must be: Excellent in explanation of problem understanding, explanation of Technologies, explanation of Scope of the work, explanation of limitation of the work, explanation of improvements

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    Configure hadoop and perform word count on an input file by using mapreduce on multiple nodes (for example - 1 master and 2 slave nodes).Compare the results obtained by changing the block size each time.

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    The most vital thing in applying the MapReduce framework to real-world problems is to identify what the keys and values are. While there are more advanced approaches, the following hint is a naïve method for inspiring your creativity. You can use the candidate median strings (of a total of 65536) as the keys, and the total matching distances of the respective candidates as the values. That means you will not get the keys from input but generate the keys (i.e., enumerating the candidate median strings) through your code on the fly. Your Map function outputs each median string paired with its total matching distance; your Reduce function reverses each key/value pair such as <k,v>  <v,k>. The output of Reduce will be a sorted list of the reversed pairs and the first...

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    Hadoop, mapreduce Finalizado left

    I need help with Hadoop, map reduce and spark. deadline is 24 hrs. please see attached files.

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    ...be used for the application created. The approach involves identifying trading signals in financial time series and capturing the risk associated to these. Such an assessment might support a subsequent evaluation of a trading strategy. Requirements: You must use: (i) Google App Engine, (ii) AWS Lambda, and (iii) one of the other scalable services in AWS: Elastic Compute Cloud (EC2), Elastic MapReduce (EMR) or – should you wish to explore – EC2 Container Service (ECS). Subsequent mentions of scalable services in this document mean Lambda plus your choice of (EC2 or EMR or ECS). ii. Your system must offer a persistent front-end through which the user will initialise (create or ‘warm up’, as necessary) and terminate (as necessary to remove any possible conti...

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    This project is mainly about tracking people which is like a social network friendship recommendation algorithm using MapReduce

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    LetterCount MR Finalizado left

    1. Write a MapReduce program to find the frequency of each letter, case insensitive, in any input user-specified files. For example, "The quick brown fox jumps over the lazy dog" as input should generate the following output (letter,count) pairs: (T, 2), (H, 1), (E, 3), etc. 2. Your program also must find the total count of letters, case insensitive, from the input. Generate one extra output pair whose key is the string "total" and whose value is the total count of all letters. 3. Test your program against the 3 attached input files. 4. The input and output will be read/written from/into HDFS. 5. Your program must consist of a single file, namely, LetterCount.java. Declare the mapper and reducer classes as inner classes.

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    1. Write a MapReduce program to find the frequency of each letter, case insensitive, in any input user-specified files. For example, "The quick brown fox jumps over the lazy dog" as input should generate the following output (letter,count) pairs: (T, 2), (H, 1), (E, 3), etc. 2. Your program also must find the total count of letters, case insensitive, from the input. Generate one extra output pair whose key is the string "total" and whose value is the total count of all letters. 3. Test your program against the 3 attached input files. 4. The input and output will be read/written from/into HDFS. 5. Your program must consist of a single file, namely, LetterCount.java. Declare the mapper and reducer classes as inner classes.

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    Teksands is looking for an experienced Trainer/Mentor on Hadoop Big Data Engineering with excellent knowledge on the following stack: Hadoop (HDFS, MapReduce) Spark Hive Kafka Only experienced candidates should apply. This is a part-time / contract role – classes in evening/flexible timings, 2-3 times per week for 1.5 hours. Mentor’s responsibility is to teach key concepts to the students, guide them in further learning, provide and guide in assignments and projects, helping them crack interviews. About Teksands: We are a Talent Solutions company helping corporates with Sourcing and Skilling for their talent needs through our flagship Bootcamp based program called Lift-Off. Our goal is to develop future-ready workforce out of fresh grads and junior engineers giving...

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    there are two data sets online retail system, have to write one mapreduce program for both data sets

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    Write a MapReduce program in Hadoop that implements the single-pass matrix multiplication.

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    Skills: Java EE, EJB, Spark, marven, ant, hadoop, spring, mapreduce etc and hope you can work with eclipse. We can connect over discord,zoom, skype anything. EC story Create an ANT project, named ec-stats, for simple descriptive statistics.

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    ...warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments (such as Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume). · Understanding of the auxiliary practical concerns in production ML systems. If you are interested and matching as per requirements, kindly share your updated CV and below details Total Experience? Relevant Experience in deep learning frameworks (such as l, Torch, Caffe, Theano) ? Python, Scala, AWS, Azure and Google cloud platforms? Machine Learning? Reporting/analytic tools and environments (such as Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).? Current Company? Current Location Flexible to work in the office? Current CTC? Expected CTC? Notice Period? (Shortlisting ...

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    1. create another table words and modify WordCount program so that it writes its input inti HBase. (explain steps and take corresponding screenshots) 2. Write a second MapReduce job which reads the output from 1) from HBase and Writes a row for each distinct count value inti HBase with the words as columns. Set the column values to 0. (explain steps and take corresponding screenshots) example input: to be or not to be example output: (1, {or:0, not:0}), (2, {to:0, be:0}) 3. Write a simple python program (bi MapReduce) which read your HBase table and prints all words for a count value which is submitted via a console parameter. I need to print all words which occur five times in the input document of 1. I have map, reduce python file and some reference documents also. t...

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    1. create another table words and modify WordCount program so that it writes its input inti HBase. (explain steps and take corresponding screenshots) 2. Write a second MapReduce job which reads the output from 1) from HBase and Writes a row for each distinct count value inti HBase with the words as columns. Set the column values to 0. (explain steps and take corresponding screenshots) example input: to be or not to be example output: (1, {or:0, not:0}), (2, {to:0, be:0}) 3. Write a simple python program (bi MapReduce) which read your HBase table and prints all words for a count value which is submitted via a console parameter. I need to print all words which occur five times in the input document of 1. I have map, reduce python file and some reference documents also. t...

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    Implement a parallel program in Java to process a set of text documents received as input, evaluating the length of the processed words, as well as arranging the documents according to the length words and the frequency with which they occur. Each word will be associated with a value, depending on the number of letters. The value of a word is determined by a formula based on Fibonacci's row, so how to explain it later. The rank of a document is calculated by summing the values of all the words in this one. In addition, the maximum length word (or words, if any) shall be laid down for each document several with the same maximum length). Following the parting process, the number of letters of each existing word in a document will be determined, obtaining a list of pairs {length, number ...

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    Implement a parallel program in Java to process a set of text documents received as input, evaluating the length of the processed words, as well as arranging the documents according to the length words and the frequency with which they occur. Each word will be associated with a value, depending on the number of letters. The value of a word is determined by a formula based on Fibonacci's row, so how to explain it later. The rank of a document is calculated by summing the values of all the words in this one. In addition, the maximum length word (or words, if any) shall be laid down for each document several with the same maximum length). Following the parting process, the number of letters of each existing word in a document will be determined, obtaining a list of pairs {length, number ...

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    . In this project, you will use the IMDB (International Movies) dataset and develop programs to get interesting insights into the dataset using Hadoop map/reduce paradigm. Please use the following links for a better understanding of Hadoop and Map/Reduce () 1. XSEDE Expanse M/R system You will be using the XSEDE Comet system for your project. Your login has been added for usage. Instructions have been given for using Comet. This is a facility supported by NSF for educational usage. Please make sure you stay within the quota for usage which is approximately 500 SU’s per team. You can install Hadoop on your laptop/desktop for developing and testing the code before you run it on Comet

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    Big Data Finalizado left

    Experience in guiding with Big Data Technology (MapReduce, Hadoop, Spark, Cassandra)

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    Entrada: tupla (id,termo) em que "id" é o identificador do documento e "termo" é uma palavra do texto já pré-processada. (Pseudocod/Python/PySpark/Spark)

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    Hi all, Looking for support on below skill set Transition of legacy ETLs with Java and Hive queries to Spark ETLs. Design and develop data processing solutions and custom ETL pipelines for varied data formats like parquet and Avro. Design, develop, test and release ETL mappings, mapplets, workflows using Streamsets, Java MapReduce, Spark and SQL. Let me know if you have experience in it

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    Desenvolvimento de algoritmo. sobre MapReduce, utilizando Pyspark/Spark...

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    Write a regular Python program and then write a mapper and reducer for both txt and csv files

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    Hello. I have pseudocode and some codes for the stripes and pairs for MapReduce. basically, there are lines of numbers, and we want to create neighbors (with the number to its right). then use the pairs and stripes map-reduce method on these. MapReduce-book-final-Jimmy+ pseudo-code is on pages 51-55 Attempting to write the pairs and stripes for MapReduce in python. was able to get the pairs mapper function to work. You need to read csv file and should (print) emit (a, b) -> count. Basically, make tuples with its neighbor and assign 1 as count. Then the reducer should the values inside the tuple (a+b). Regularly, for map-reduce, we strip the lines and read documents/files, and do things with them. Hope it will make sense. Thank you.

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    hello. I have pseudocode for the stripes and pairs for MapReduce. basically, there are lines of numbers, and we want to create neighbors (with the number to its right). then use the pairs and stripes map-reduce method on these. MapReduce-book-final-Jimmy+ pseudo-code is on pages 51-55 attempting to write the pairs and stripes for MapReduce in python. was able to get the pairs mapper function to work.

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    Principales artículos de la comunidad mapreduce