As a pioneering company in Cloudera Hadoop technology, Big data is looking forward to share their own experience, and deliver comprehensive training courses to benefit manager, developer and system administrator. We prepare expert content and practice for attendees to understand the real-world challenges of building, deploying and managing the Hadoop technologie.(Hadoop, Big data,Analytics, etc.)
Hadoop Training Course Content:
1. Understanding Big Data – What is Big Data ?
Real world issues with BIG Data – Ex: How facebook manage peta bytes of data.
Will regular traditional approach works?
2. How Hadoop Evolved
Back to Hadoop evolution.
The ecosystem and stack: HDFS, MapReduce, Hive, Pig…
Cluster architecture overview
3. Environment for Hadoop development
Hadoop distribution and basic commands
Eclipse development
4. Understanding HDFS
Command line and web interfaces for HDFS
Exercises on HDFS Java API
5. Understanding MapReduce
Core Logic: move computation, not data
Base concepts: Mappers, reducers, drivers
The MapReduce Java API (lab)
6. Real-World MapReduce
Optimizing with Combiners and Partitioners (lab)
More common algorithms: sorting, indexing and searching (lab)
Relational manipulation: map-side and reduce-side joins (lab)
Chaining Jobs
Testing with MRUnit
7. Higher-level Tools
Patterns to abstract “thinking in MapReduce”
The Cascading library (lab)
The Hive database (lab)
Interested ? Enroll into our online Apache Hadoop training program now.
at 04:53 |
As a pioneering company in Cloudera Hadoop technology, Big data is looking forward to share their own experience, and deliver comprehensive training courses to benefit manager, developer and system administrator. We prepare expert content and practice for attendees to understand the real-world challenges of building, deploying and managing the Hadoop technologie.(Hadoop, Big data,Analytics, etc.)
Hadoop Training Course Content:
1. Understanding Big Data – What is Big Data ?
Real world issues with BIG Data – Ex: How facebook manage peta bytes of data.
Will regular traditional approach works?
2. How Hadoop Evolved
Back to Hadoop evolution.
The ecosystem and stack: HDFS, MapReduce, Hive, Pig…
Cluster architecture overview
3. Environment for Hadoop development
Hadoop distribution and basic commands
Eclipse development
4. Understanding HDFS
Command line and web interfaces for HDFS
Exercises on HDFS Java API
5. Understanding MapReduce
Core Logic: move computation, not data
Base concepts: Mappers, reducers, drivers
The MapReduce Java API (lab)
6. Real-World MapReduce
Optimizing with Combiners and Partitioners (lab)
More common algorithms: sorting, indexing and searching (lab)
Relational manipulation: map-side and reduce-side joins (lab)
Chaining Jobs
Testing with MRUnit
7. Higher-level Tools
Patterns to abstract “thinking in MapReduce”
The Cascading library (lab)
The Hive database (lab)
Interested ? Enroll into our online Apache Hadoop training program now.
Magnific Training (magnifictraining.com)having a high edge On Hadoop/Big Data Online Training. A fully Dedicate Hadoop online Training Center,
Having A massive Experience of Around 8+ Years of Online Training Trained many clints/Professional/students all over the Globe.
So you are going to need an Hadoop admin:
Who are the candidates for the position? Best option is to hire an experienced Hadoop admin. In 2-3 years no one will even consider doing anything else. But right now there is an extreme shortage of Hadoop admins, so we need to consider less perfect candidates.
The usual suspects tend to be: Junior java developers, sys admins, storage admins and DBAs.
When we get to the operations personel – storage admins are usually out of consideration because their skillset is too unique and valuable at other parts of the organization. I’ve never seen a storage admin who became an Hadoop admin, or any place where it was even seriously considered.
I’ve seen both DBAs and sysadmins becoming excellent Hadoop admins. In my highly biased opinions, DBAs have some advantages:
Everyone knows DBA stands for “Default Blame Acceptor”. Since the database is always blamed, DBAs typically have great troubleshooting skills, processes and instincts. All those are critical for good cluster admins.
DBAs are used to manage a system with millions of knobs to turn, all of which have critical impact on the performance and availability of the system. Hadoop is similar to databases in this sense – tons of configurations to fine-tune.
DBAs, much more than sysadmins, are highly skilled in keeping developers in check and making sure no one accidentally causes critical performance issues on an entire system. Critical skill when managing Hadoop clusters.
DBA experience with DWH (especially Exadata) is very valuable. There are many similarities between DWH workloads and Hadoop workloads, and similar principles guide the management of the system.
DBAs tend to be really good about writing their own monitoring jobs when needed. Every production database system I’ve seen has crontab file full of customized monitors and maintenance jobs. This skill continues to be critical for Hadoop system.
To be fair, sysadmins also have important advantages:
They typically have more experience managing huge number of machines. Much more so than DBAs. They have experience working with configuration management and deployment tools (puppet, chef), which is absolutely critical when managing large clusters. They can feel more comfortable digging in the OS and network when configuring and troubleshooting systems, which is important part of Hadoop administration.
You can attend 1st 2 classes or 3 hours for free. once you like the classes then you can go for registration.
Duration for course is 30 days or 45 hours and special care will be taken. It is a one to one training with hands on experience.
* Resume preparation and Interview assistance will be provided.
For any further details please contact +91-9052666559 or visit www.magnifictraining.com
please mail us all queries to info@magnifictraining.com
at 03:08 |
Magnific Training (magnifictraining.com)having a high edge On Hadoop/Big Data Online Training. A fully Dedicate Hadoop online Training Center,
Having A massive Experience of Around 8+ Years of Online Training Trained many clints/Professional/students all over the Globe.
So you are going to need an Hadoop admin:
Who are the candidates for the position? Best option is to hire an experienced Hadoop admin. In 2-3 years no one will even consider doing anything else. But right now there is an extreme shortage of Hadoop admins, so we need to consider less perfect candidates.
The usual suspects tend to be: Junior java developers, sys admins, storage admins and DBAs.
When we get to the operations personel – storage admins are usually out of consideration because their skillset is too unique and valuable at other parts of the organization. I’ve never seen a storage admin who became an Hadoop admin, or any place where it was even seriously considered.
I’ve seen both DBAs and sysadmins becoming excellent Hadoop admins. In my highly biased opinions, DBAs have some advantages:
Everyone knows DBA stands for “Default Blame Acceptor”. Since the database is always blamed, DBAs typically have great troubleshooting skills, processes and instincts. All those are critical for good cluster admins.
DBAs are used to manage a system with millions of knobs to turn, all of which have critical impact on the performance and availability of the system. Hadoop is similar to databases in this sense – tons of configurations to fine-tune.
DBAs, much more than sysadmins, are highly skilled in keeping developers in check and making sure no one accidentally causes critical performance issues on an entire system. Critical skill when managing Hadoop clusters.
DBA experience with DWH (especially Exadata) is very valuable. There are many similarities between DWH workloads and Hadoop workloads, and similar principles guide the management of the system.
DBAs tend to be really good about writing their own monitoring jobs when needed. Every production database system I’ve seen has crontab file full of customized monitors and maintenance jobs. This skill continues to be critical for Hadoop system.
To be fair, sysadmins also have important advantages:
They typically have more experience managing huge number of machines. Much more so than DBAs. They have experience working with configuration management and deployment tools (puppet, chef), which is absolutely critical when managing large clusters. They can feel more comfortable digging in the OS and network when configuring and troubleshooting systems, which is important part of Hadoop administration.
You can attend 1st 2 classes or 3 hours for free. once you like the classes then you can go for registration.
Duration for course is 30 days or 45 hours and special care will be taken. It is a one to one training with hands on experience.
* Resume preparation and Interview assistance will be provided.
For any further details please contact +91-9052666559 or visit www.magnifictraining.com
please mail us all queries to info@magnifictraining.com
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