This document provides an introduction and overview of an Advanced Operating Systems course. The course will take approximately 5 weeks to complete and have 11 lessons. It will cover topics like abstractions, OS structure, virtualization, parallelism, distributed systems, and security. Each lesson will be released weekly and students are expected to spend around 6 hours per week to complete the material.
The document discusses a presentation on real-time analytics using Apache Storm. It covers basic Storm theory and setup, using Twitter streams with Storm, practices building streaming joins and exclamation topologies, and concludes with discussing student project teams analyzing sentiment, geography, ebola topics, and their use of tools like OpenCV.
Storm is an open source distributed real-time computation system from Apache that allows processing streams of data in real-time. It is composed of spouts which act as sources of data streams and bolts which perform processing on the data. Topologies define the layout of spouts and bolts and how data flows between them. Common groupings in Storm include shuffle, fields, all, and global groupings which determine how data is distributed between processing tasks.
[Taewoo Kim] Real-Time Analytics with Apache StormTaewoo Kim
This document summarizes a study on real-time analytics using Apache Storm. It outlines four parts to the study: 1) learning the theory, setup, and basics of Storm, 2) using Storm with Twitter streams, 3) going beyond basic Storm concepts with an example join, and 4) participating in a Storm project and hackathon. It then describes two practices - parsing tweet URLs and tracking top hashtags - to demonstrate Storm's use for real-time analytics on Twitter data streams.
This document outlines a plan to study real-time analytics using Apache Storm. It describes setting up Storm and completing basic tutorials on processing streaming data. The plan is to first learn Storm's theory and setup, then complete examples using Twitter streams and more advanced Storm techniques before participating in a Storm hackathon project.
This document provides an introduction and overview of an Advanced Operating Systems course. The course will take approximately 5 weeks to complete and have 11 lessons. It will cover topics like abstractions, OS structure, virtualization, parallelism, distributed systems, and security. Each lesson will be released weekly and students are expected to spend around 6 hours per week to complete the material.
The document discusses a presentation on real-time analytics using Apache Storm. It covers basic Storm theory and setup, using Twitter streams with Storm, practices building streaming joins and exclamation topologies, and concludes with discussing student project teams analyzing sentiment, geography, ebola topics, and their use of tools like OpenCV.
Storm is an open source distributed real-time computation system from Apache that allows processing streams of data in real-time. It is composed of spouts which act as sources of data streams and bolts which perform processing on the data. Topologies define the layout of spouts and bolts and how data flows between them. Common groupings in Storm include shuffle, fields, all, and global groupings which determine how data is distributed between processing tasks.
[Taewoo Kim] Real-Time Analytics with Apache StormTaewoo Kim
This document summarizes a study on real-time analytics using Apache Storm. It outlines four parts to the study: 1) learning the theory, setup, and basics of Storm, 2) using Storm with Twitter streams, 3) going beyond basic Storm concepts with an example join, and 4) participating in a Storm project and hackathon. It then describes two practices - parsing tweet URLs and tracking top hashtags - to demonstrate Storm's use for real-time analytics on Twitter data streams.
This document outlines a plan to study real-time analytics using Apache Storm. It describes setting up Storm and completing basic tutorials on processing streaming data. The plan is to first learn Storm's theory and setup, then complete examples using Twitter streams and more advanced Storm techniques before participating in a Storm hackathon project.
Storm is a distributed real-time computation system for processing streaming data. It provides abstractions called topologies, spouts, and bolts. A topology defines the flow of data between spouts, which act as sources, and bolts, which perform processing. Storm distributes the computation across a cluster of machines coordinated by a master node called Nimbus and worker nodes called supervisors.
INTELLIPAAT (www.intellipaat.com) is a young dynamic online training provider driving Education for Employ-ability & Career advancement across the globe Known as a "one stop, training shop" for high end technical training. Learn any Niche Business Intelligence, Database and BigData ,cloud computing technologies:
Business Intelligence/Database
Tableau Server, Buisness Object, Spotfire, Datastage, OBIEE, Qlikview, Hyperion, Microstartegy, Pentaho, Cognos, Informatica, Talend,Oracle Developer, Oracle DBA, DataModeling, Sap Business Object, Sap Hana etc..
BigData/CloudComputing
Spark, Storm, Scala, Mahout(Machine Learning),Hadoop, Cassandra, Hbase, Solr, Splunk, openstack etc.
Since we started our journey, we have trained over 1,20,000+ professionals with 50 corporate clients across the globe. Intellipaat has offices in India ( Jaipur , Bangalore) .US, UK, Canada.
INTELLIPAAT (www.intellipaat.com) is a young dynamic online training provider driving Education for Employ-ability & Career advancement across the globe Known as a "one stop, training shop" for high end technical training. Learn any Niche Business Intelligence, Database and BigData ,cloud computing technologies:
Business Intelligence/Database
Tableau Server, Buisness Object, Spotfire, Datastage, OBIEE, Qlikview, Hyperion, Microstartegy, Pentaho, Cognos, Informatica, Talend,Oracle Developer, Oracle DBA, DataModeling, Sap Business Object, Sap Hana etc..
BigData/CloudComputing
Spark, Storm, Scala, Mahout(Machine Learning),Hadoop, Cassandra, Hbase, Solr, Splunk, openstack etc.
Since we started our journey, we have trained over 1,20,000+ professionals with 50 corporate clients across the globe. Intellipaat has offices in India ( Jaipur , Bangalore) .US, UK, Canada.
The key objectives of this online Big Data Hadoop Tutorial and training program are to enable developers to:
Programming in YARN (MRv2) latest version of Hadoop Release 2.0
Implementation of HBase, MapReduce Integration, Advanced Usage and Advanced Indexing.
Advance Map Reduce exercises – examples of Facebook sentiment analysis , LinkedIn shortest path algorithm, Inverted indexing.
Derive an insight into the field of Data Science
Understand the Apache Hadoop framework
Learn to work with Hadoop Distributed File System (HDFS)
Implement Multi node cluster using 3-4 instances of Amazon ec2.
Learn how MapReduce interacts with data and processes them
Ability to design and develop applications involving large data using Hadoop eco system.
Differentiate between new as well as old APIs for Hadoop
Understand how YARN engages in managing compute resources into clusters
Last but not the least, the Hadoop online tutorial program prepares programmers for better career opportunities in the world of Big Data!
This document summarizes sessions from the Samsung Open Source Conference from October 26-28. It discusses the Linux kernel boot process, IoT frameworks like IoT.js and JerryScript.js, and the Apache Horn project for big data and deep learning using a neuron-centric approach. The Linux kernel boot process initiates start_kernel() and mm_init() from over 15 million lines of code. IoT.js and JerryScript.js provide lighter alternatives to Node.js for IoT applications. Apache Horn is an open source project for deep learning that focuses on neurons.
Storm is a distributed real-time computation system for processing streaming data. It provides abstractions called topologies, spouts, and bolts. A topology defines the flow of data between spouts, which act as sources, and bolts, which perform processing. Storm distributes the computation across a cluster of machines coordinated by a master node called Nimbus and worker nodes called supervisors.
INTELLIPAAT (www.intellipaat.com) is a young dynamic online training provider driving Education for Employ-ability & Career advancement across the globe Known as a "one stop, training shop" for high end technical training. Learn any Niche Business Intelligence, Database and BigData ,cloud computing technologies:
Business Intelligence/Database
Tableau Server, Buisness Object, Spotfire, Datastage, OBIEE, Qlikview, Hyperion, Microstartegy, Pentaho, Cognos, Informatica, Talend,Oracle Developer, Oracle DBA, DataModeling, Sap Business Object, Sap Hana etc..
BigData/CloudComputing
Spark, Storm, Scala, Mahout(Machine Learning),Hadoop, Cassandra, Hbase, Solr, Splunk, openstack etc.
Since we started our journey, we have trained over 1,20,000+ professionals with 50 corporate clients across the globe. Intellipaat has offices in India ( Jaipur , Bangalore) .US, UK, Canada.
INTELLIPAAT (www.intellipaat.com) is a young dynamic online training provider driving Education for Employ-ability & Career advancement across the globe Known as a "one stop, training shop" for high end technical training. Learn any Niche Business Intelligence, Database and BigData ,cloud computing technologies:
Business Intelligence/Database
Tableau Server, Buisness Object, Spotfire, Datastage, OBIEE, Qlikview, Hyperion, Microstartegy, Pentaho, Cognos, Informatica, Talend,Oracle Developer, Oracle DBA, DataModeling, Sap Business Object, Sap Hana etc..
BigData/CloudComputing
Spark, Storm, Scala, Mahout(Machine Learning),Hadoop, Cassandra, Hbase, Solr, Splunk, openstack etc.
Since we started our journey, we have trained over 1,20,000+ professionals with 50 corporate clients across the globe. Intellipaat has offices in India ( Jaipur , Bangalore) .US, UK, Canada.
The key objectives of this online Big Data Hadoop Tutorial and training program are to enable developers to:
Programming in YARN (MRv2) latest version of Hadoop Release 2.0
Implementation of HBase, MapReduce Integration, Advanced Usage and Advanced Indexing.
Advance Map Reduce exercises – examples of Facebook sentiment analysis , LinkedIn shortest path algorithm, Inverted indexing.
Derive an insight into the field of Data Science
Understand the Apache Hadoop framework
Learn to work with Hadoop Distributed File System (HDFS)
Implement Multi node cluster using 3-4 instances of Amazon ec2.
Learn how MapReduce interacts with data and processes them
Ability to design and develop applications involving large data using Hadoop eco system.
Differentiate between new as well as old APIs for Hadoop
Understand how YARN engages in managing compute resources into clusters
Last but not the least, the Hadoop online tutorial program prepares programmers for better career opportunities in the world of Big Data!
This document summarizes sessions from the Samsung Open Source Conference from October 26-28. It discusses the Linux kernel boot process, IoT frameworks like IoT.js and JerryScript.js, and the Apache Horn project for big data and deep learning using a neuron-centric approach. The Linux kernel boot process initiates start_kernel() and mm_init() from over 15 million lines of code. IoT.js and JerryScript.js provide lighter alternatives to Node.js for IoT applications. Apache Horn is an open source project for deep learning that focuses on neurons.
3. 1. 아침, 점심, 저녁 식단보기
- 2 -
- 어플리케이션 실행 시간에 맞는 식단을 제공
>> 9시 이전 : 아침, 09~13시 : 점심, 13~19시 : 저녁
- 선택한 식단을 History에 저장
>> 라디오 버튼을 통해 선택 후 저장
4. 2. 주간 식단보기
- 3 -
- 하루의 식단 뿐만 아니라 한 주의 식단표를 확인가능
>> 해당 날짜를 포함하는 한 주의 요일 선택 화면 제공
- 원하는 요일에 대한 버튼을 누르면 해당 요일의 식단표 제공
>> 점심 기준으로 제공, 라디오 버튼 비활성화
5. 3. 식사기록 보기
- 4 -
- 달력을 통해 자신이 먹은 식단을 확인 가능
>> 각 요일 별, 먹은 식단에 대한 정보 제공
>> 이미지와 칼로리를 통해 간단한 정보를 제공
- 특정 요일을 선택하여 자세한 내용 확인 가능
6. One Week Project #2
- 식단표에 대한 기준 작성
>> 식당마다 식단표를 작성하는 형식이 다르기 때문에 기준이 필요
- Android Studio 설치 및 개발 환경 구성
>> Official IDE for Android
>> SQLite 또는 Amazon EC2 Server
- Application Layout 구현
- 5 -