), my personal direction is actually big data/distributed computing, but big data too much to use in Java, So Java also learned well: d[1] laying the groundwork (with a problem when learning) (1) Language: Solid to play a good Java Foundation, focus on the concurrency and network parts, understand some common design patterns (do not back, need experience to understand). (2) Data structures and algorithms: If you cannot organize data, manipulate the data, and solve problems naturally cannot be im
; Tips - --don't fall into the same, growing problem of C + +, leaving too many choices and no clear best practices. This causes everyone to choose a different subset. To provide guidance for adaptation. and remember, the anti-bad design features are just as important as adding new features-it's brutal. --Consider splitting the language to create a workable standard for the resulting environment. Saving money for the academic world is a wise choice. To meet the needs of enterprises, to achie
should be applied to a large scale of low CPU and memory consumption applications.
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Easy to develop
Quick, but there are no other frames fast
Supports non-blocking I/O based on Netty. It's good to handle remote calls in parallel.
The community is big.
Fast Project building and start-up
of modular
Mvc
REST, Json/xml, Web Sockets, non-blocking I/O
Just refresh the browser to see the latest changes
Support Async
There are books published.
-ins
Open the Idea,config to find plugins:Search Scala:Iv. creating the SBT project in idea
New project, select SCALA->SBT:To configure the project name and path:
New Scala Class:
Kind Select object, note, do not select class here.
Write a Hello World:
Run (if the above file chooses class, there is no Scala file running to the command):
Results:V. Spark MAVEN Project
Write the spark program in the MAVEN project and add the coordinates of the spark:
trackers are listed in chronological order.
NAME CODE REFERENCE CPF CPF P. Pe 虂 rez, C. Hue, J. Vermaak, and M. Gangnet. COLOR-BASED probabilistic tracking. In ECCV, 2002. KMS kms D. Comaniciu, V. Ramesh, and P. Meer. KERNEL-BASED Object Tracking. Pami, 25 (5): 564 transmission 577, 2003. SMS SMS R. Collins. MEAN-SHIFT Blob tracking through Scale space. In CVPR, 2003. Vr-v vivid/vr R. Collins, Y. Liu, and M. Leordeanu. Online Selection of discriminative tracking Features. Pami, 27 (10): 1631 t
the Spark-assembly-1.5.0-hadoop2.4.0.jar under the Lib this package.
4.3 New Scala project, File-> new project-> Scala-> next fill in name and SDK-> finish.
4.4 On the project page "File"-> "Project Structure"-> "libraries", point "+", select Java, Find the Spark-assembly-1.5.0-hadoop2.4.0.jar import so that you can write a spark Scala program.
4.5 Most of the time we need to use MAVEN or SBT management dependencies, where I use Maven. Intellij15.0 i
projects to gain experience. The problem with MySQL and time series data sharding (fragmentation) is that there is always a slice too hot. In addition, the problem of read replication latency is encountered because you want to insert concurrency on slave.
In addition, a common service framework has been developed: It takes a lot of time to solve the operational dimension of distributed system Management. A rails scaffolding is developed for the service, and the internal template is used to star
file, here are 5 copiesb) Recovery window of 7 days--Indicates that you want the database to be restored to a few days ago.c) None--Indicates that a retention policy is not requiredNOTES: a) and b) are mutually exclusive relationships.2) CONFIGURE BACKUP optimization ...-In theory, backup optimization works only for read-only table spaces or offline table spaces. Of course, the archived log files that have already been backed up will also be skipped, and the default is off3) CONFIGURE DEFAULT D
Recently, when processing data, you need to join the raw data with Redis data, in the process of reading Redis, encountered some problems, by the way to make a note, hoping for other students also helpful. During the experiment, it was not stressful to read Redis one at a time when the amount of data was 100,000 levels, but when the amount of data reached tens, the problem arose, even with the mappartitions of Spark. Therefore, consider using Redis's pipeline (if you have a better approach, plea
===========================================Original link: Scala to MongoDB additions and deletions to the operation reproduced please specify the source! ===========================================Environment dependent: jdk1.8, Scala 2.12, IdeaMongoDB driver:3.1.1. Note that the MONGO for Scala driver involves multiple jars (such as) and relies on Mongo-java-driver.jarThe SBT used here relies on management, adding dependencies directly to BUILD.SBT:
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Android Barcode Generator
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Zbar
ZXing
Build the System
Apache Ant
Apache Maven
Buck
Gant
Gradle
Leiningen
SBt
Press button
Android Circle Button
Android-bootstrap
Circular Progress Button
Flat Button
Process Button
Progressbutton
Psgradientbuttons
Th-progressbutton
Csv
Csv
Jdk7Http://www.oracle.com/technetwork/java/javase/downloads/jdk7-downloads-1880260.htmlscala2.10.4Http://www.scala-lang.org/download/2.10.4.htmlScala for Eclipse plugin downloadSo I installed it through help->install new software. Add Input URL:The URL is connected from here (official website) to (:Http://scala-ide.org/download/prev-stable.htmlFor Scala 2.10.4Http://download.scala-ide.org/sdk/helium/e38/scala210/stable/siteEclipse 3.8-4.3 (Juno and Kepler) for Scala 2.11.2Http://download.scala-i
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