Map Reduce is a powerful programming model designed to process and analyze large, distributed datasets. It divides the large datasets into multiple parts and assigns them to individual processing nodes, allowing for faster and easier data processing. A Map Reduce Developer can help you create complex systems to glean valuable insights from your data, optimize system resources, and improve performance.
The wide array of applications is a testament to the value of implementing Map Reduce on projects. You can use it for web crawling, data mining, machine learning, natural language processing, and more. Our Map Reduce Developers are top-notch experts who specialize in open source Java frameworks such as Hadoop and Apache Spark, multi-valued large data sets that incorporate various processes like search algorithms and sentiment analytics. Our developers have also worked on projects with Docker containerization and using cloud platforms such as Amazon Web Services.
Here’s some projects that our expert Map Reduce Developers made real:
- Data analysis to better understand trends in the markets
- Automatically search for certain items in a massive dataset
- Get real time insight from streaming data
- Automatically process large amounts of text from documents or unstructured sources
- Extract ideas from massive datasets or predict outcomes by training models with ML algorithms
- Ensure data consistency across repositories
Our Map Reduce Developers provide efficient solutions that help maximize the use of your data efficiently. Through distributed computing techniques, our Map Reduce Developers can construct systems with scalability so your business won’t outgrow its infrastructure. With up to date knowledge fr0m open source frameworks, our developers consistently push the envelope on what is possible by employing the latest research practices and known technologies making sure you stay ahead of the curve.
At Freelancer.com you can hire a highly professional Map Reduce Developer to make a real difference in your project. Post your own project today to get expert help quickly and easily!
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BigData Task 1. Create a Scalable data pipeline using any one framework- a. Pyspark, b. Scala Spark c. logstash 2. Data flow pipelines should have plugable transformation functions. And write sample transformations. a. Group By some Measure b. Join some other Data Pipeline or static datasets 3. Read/Write should be considering connector based design to make data flow from/to S3, GCP, Files, Hadoop, SQL DB or file storage (any one sample good) 4. Read/Write Data in multiple formats Json, Parquet, gZip 5. Publish Data Pipeline as application. Build and Deploy package definition and development. Deployment package should be separate from the source code. 6. Write CICD Notes and Readme file to simulate pipeline in test environment
HDFS Setup Configuration: 1 NameNode 3 DataNodes 1 SecondaryNameNode Requirements: Assuming your team has three students: Tom (999900012), Jerry (999900034), Mike (999900056) Configure the hostname of each DataNode: Hostname of DataNode 1: Tom Hostname of DataNode 2: Jerry Hostname of DataNode 3: Mike Set the last two digits of the IP address of each DataNode: IP address of DataNode 1: IP address of DataNode 2: IP address of DataNode 3: Submission Requirements: Submit the following screenshots: Use commands to create three directories on HDFS, named after the first name of each team member. Use commands to upload the Hadoop package to HDFS. Use commands to show the IP addresses of all DataNodes. Provide detailed information (ls -l) of the blocks on each DataNode. Provi...
Job Title: Informatica Cloud MDM Architect/Senior Developer Location: HYD/Remote Duration: Full Time Required Skills: • At least 12+Years of experience in designing, developing, and implementing Informatica MDM solutions with at least one end to end project experience using Informatica Cloud. • Experience in architecting Informatica Master data management in a large enterprise integrating diverse ERP systems (such as Salesforce, SAP) and implementing an effective, efficient, and easy to maintain batch/real time/near real time integrations. • Strong experience in Informatica SaaS Multidomain MDM components and their interaction for solutioning – Cloud Data Quality (CDQ), Cloud Data Integration (CDI), Cloud Application Integration (CAI),...