Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
SlideShare a Scribd company logo

Stay fresh

•Download as PPTX, PDF•
•
Ahmed Mohamed
Ahmed Mohamed

This document discusses various programming language trends including functional programming languages like Haskell, purely object-oriented languages, and Scala. It also covers database trends like NoSQL databases Cassandra and MongoDB. Programming tools like Docker and Vagrant are mentioned. The document discusses paradigms like static vs dynamic typing and strong vs weak typing. It provides examples and resources for languages including Haskell, Erlang, Scala, and databases like Cassandra.

1 of 36
Stay Fresh
Agenda Morphy Law? Technology Trend a. Programming languages b. Database c. Tools Topics a. Continuous Integration b. Test Driven c. Software as a service (saas) WorkDay d. Platform as a service (paas) Hadoop,apprenda e. Infrastructure as a service (iaas) AWS,Microsoft Azure
Murphy Law Anything that can go wrong Will go wrong :)
Programming Languages: Scala Erlang Haskel TypeScript Paradigm: Functional Programming Pure Object Oriented
Pure Object Oriented Languages called "pure" OO languages, because everything in them is treated consistently as an object, from primitives such as characters and punctuation, all the way up to whole classes, prototypes, blocks, modules, etc. They were designed specifically to facilitate, even enforce, OO methods. Examples: Eiffel, Emerald, JADE, Obix, Ruby, Scala, Smalltalk, Self.
Pure Object Oriented Languages called "pure" OO languages, because everything in them is treated consistently as an object, from primitives such as characters and punctuation, all the way up to whole classes, prototypes, blocks, modules, etc. They were designed specifically to facilitate, even enforce, OO methods. Examples: Eiffel, Emerald, JADE, Obix, Ruby, Scala, Smalltalk, Self.
Pure Functional Pure functional programming languages do not allow side effects (and are therefore of little use in practice because any useful program does have side effects, e.g. when it interacts with the external world). Example Haskell
Pure Functional In computer programming, a function may be considered a pure function if both of the following statements about the function hold: 1. The function always evaluates the same result value given the same argument value(s). The function result value cannot depend on any hidden information or state that may change while program execution proceeds or between different executions of the program, nor can it depend on any external input from I/O devices (usually—see below). 1. Evaluation of the result does not cause any semantically observable side effect or output, such as mutation of mutable objects or output to I/O devices (usually—see below).
Java is not a pure Object oriented language, It’s "Hybrid" language or FULLY OOP. For any language to be pure object oriented it must follow these 6 points strictly... 1) It must have full support for Encapsulation and Abstraction 2) It must support Inheritance 3) It must support Polymorphism 4) All predefined types must be Objects 5) All user defined types must be Objects 6) Lastly, all operations performed on objects must be only through methods exposed at the objects.
Static VS Dynamic Static/Dynamic typing is about when type information is aquired (Either at compile time or at runtime) Strong VS Weak Strong/Weak typing is about how strictly types are distinguished (e.g. whether the language tries to do implicit conversion from strings to numbers). PHP => Dynamic & Weak Ruby => Dynamic & Strong Java =>Static & Strong
References https://en.wikipedia.org/wiki/Strong_and_weak_typing https://pythonconquerstheuniverse.wordpress.com/2009/10/03/static-vs-dynamic-typing-of- programming-languages/
Statically typed Purely functional Type inference Concurrent Lazy Packages Haskell
Every expression in Haskell has a type which is determined at compile time. All the types composed together by function application have to match up. If they don't, the program will be rejected by the compiler. Types become not only a form of guarantee, but a language for expressing the construction of programs. Statically typed
You don't have to explicitly write out every type in a Haskell program. Types will be inferred by unifying every type bidirectionally. However, you can write out types if you choose, or ask the compiler to write them for you for handy documentation. Type inference
Every function in Haskell is a function in the mathematical sense (i.e., "pure"). Even side-effecting IO operations are but a description of what to do, produced by pure code. There are no statements or instructions, only expressions which cannot mutate variables (local or global) nor access state like time or random numbers. Purely functional
Haskell lends itself well to concurrent programming due to its explicit handling of effects. Its flagship compiler, GHC, comes with a high-performance parallel garbage collector and light-weight concurrency library containing a number of useful concurrency primitives and abstractions. Concurrent
Functions don't evaluate their arguments. This means that programs can compose together very well, with the ability to write control constructs (such as if/else) just by writing normal functions. The purity of Haskell code makes it easy to fuse chains of functions together, allowing for performance benefits. Lazy
Haskell Resources Haskell Website Haskell by Example Haskell Wiki Haskell for all School of Haskell
Scala General purpose programming language Multi-paradigm language (functional & object oriented) Very strong static type system Very rich language Compiled language Run in JVM Can use any java package inside it directly 2003
Scala In Enterprise
Scala Example
Scala Resources https://github.com/lauris/awesome-scala https://www.playframework.com/ http://www.scala-lang.org/
Erlang First release 1986, in Ericsson Company While threads require external library support in most languages, Erlang provides language-level features for creating and managing processes with the aim of simplifying concurrent programming. Though all concurrency is explicit in Erlang, processes communicate using message passing instead of shared variables, which removes the need for explicit locks (a locking scheme is still used internally by the VM) Why Erlang => http://veldstra.org/whyerlang/
Thread VS Process 1. Threads are easier to create than processes since they don't require a separate address space. 2. Multithreading requires careful programming since threads share data structures that should only be modified by one thread at a time. Unlike threads, processes don't share the same address space. 3. Threads are considered lightweight because they use far less resources than processes. 4. Processes are independent of each other. Threads, since they share the same address space are interdependent, so caution must be taken so that different threads don't step on each other. This is really another way of stating #2 above. 5. A process can consist of multiple threads.
Erlang handle very large number of concurrent activities be easily distributable over a network of computers be fault-tolerant to both software & hardware errors scale with the number of machines on the network be upgradeable & reconfigurable without having to stop & restart be responsive to users within certain strict timeframes stay in continuous operation for many years
Erlang Example
Erlang Resource https://github.com/drobakowski/awesome-erlang
Database Trend 1. BigData and Hadoop a. MapReduce 2. NoSql Databases a. Cassandra b. MongoDB c. RethinkDB 3. Full Text Search a. ElasticSearch
Column Oriented Database A column-oriented DBMS is a database management system (DBMS) that stores data tables as sections of columns of data rather than as rows of data. In comparison, most relational DBMSs store data in rows. This column-oriented DBMS has advantages for data warehouses, clinical data analysis, customer relationship management (CRM) systems, and library card catalogs, and other ad hoc inquiry systems where aggregates are computed over large numbers of similar data items.
Cassandra Massively scalable partitioned row store masterless architecture linear scale performance no single points of failure read/write support across multiple datacenters & cloud availability zones. API / Query Method: CQL and Thrift, replication: peer-to-peer, written in: Java, Concurrency: tunable consistency built-in data compression MapReduce support, primary/secondary indexes
Cassandra Decentralized Every node in the cluster has the same role. There is no single point of failure. Data is distributed across the cluster (so each node contains different data), but there is no master as every node can service any request. Supports replication and multi datacenter replication Replication strategies are configurable. Cassandra is designed as a distributed system, for deployment of large numbers of nodes across multiple data centers. Key features of Cassandra’s distributed architecture are specifically tailored for multiple-data center deployment, for redundancy, for failover and disaster recovery. Scalability Read and write throughput both increase linearly as new machines are added, with no downtime or interruption to applications. Fault-tolerant Data is automatically replicated to multiple nodes for fault-tolerance. Replication across multiple data centers is supported. Failed nodes can be replaced with no downtime.
Cassandra Tunable consistency Writes and reads offer a tunable level of consistency, all the way from "writes never fail" to "block for all replicas to be readable", with the quorum level in the middle MapReduce support Cassandra has Hadoop integration, with MapReduce support. There is support also for Apache Pig and Apache Hive. Query language Cassandra introduces CQL (Cassandra Query Language), a SQL-like alternative to the traditional RPC interface. CQL is simple API meant for accessing Cassandra.
ReThinkDB NoSql for real time web applications. Powerful query language Very easy UI Scale in seconds (r.table('games').reconfigure(shards=5, replicas=3)) Suitable for Web + mobile apps Multiplayer games Real time marketplaces
Tools Docker Vagrant Sass / Less Gulp / Grant Ansible / chef / Puppet Jenkins Zmq / RabbitMq / Kafka
Your Language SUCKS https://wiki.theory.org/YourLanguageSucks
Extra Steps Read => Read =>Read=>...... More Knowledge more powerful More Knowledge more productive Follow developers in github Read others source code Answers questions in Stackoverflow subscribe to any learning source packtpub

More Related Content

Stay fresh

  • 2. Agenda Morphy Law? Technology Trend a. Programming languages b. Database c. Tools Topics a. Continuous Integration b. Test Driven c. Software as a service (saas) WorkDay d. Platform as a service (paas) Hadoop,apprenda e. Infrastructure as a service (iaas) AWS,Microsoft Azure
  • 3. Murphy Law Anything that can go wrong Will go wrong :)
  • 5. Pure Object Oriented Languages called "pure" OO languages, because everything in them is treated consistently as an object, from primitives such as characters and punctuation, all the way up to whole classes, prototypes, blocks, modules, etc. They were designed specifically to facilitate, even enforce, OO methods. Examples: Eiffel, Emerald, JADE, Obix, Ruby, Scala, Smalltalk, Self.
  • 6. Pure Object Oriented Languages called "pure" OO languages, because everything in them is treated consistently as an object, from primitives such as characters and punctuation, all the way up to whole classes, prototypes, blocks, modules, etc. They were designed specifically to facilitate, even enforce, OO methods. Examples: Eiffel, Emerald, JADE, Obix, Ruby, Scala, Smalltalk, Self.
  • 7. Pure Functional Pure functional programming languages do not allow side effects (and are therefore of little use in practice because any useful program does have side effects, e.g. when it interacts with the external world). Example Haskell
  • 8. Pure Functional In computer programming, a function may be considered a pure function if both of the following statements about the function hold: 1. The function always evaluates the same result value given the same argument value(s). The function result value cannot depend on any hidden information or state that may change while program execution proceeds or between different executions of the program, nor can it depend on any external input from I/O devices (usually—see below). 1. Evaluation of the result does not cause any semantically observable side effect or output, such as mutation of mutable objects or output to I/O devices (usually—see below).
  • 9. Java is not a pure Object oriented language, It’s "Hybrid" language or FULLY OOP. For any language to be pure object oriented it must follow these 6 points strictly... 1) It must have full support for Encapsulation and Abstraction 2) It must support Inheritance 3) It must support Polymorphism 4) All predefined types must be Objects 5) All user defined types must be Objects 6) Lastly, all operations performed on objects must be only through methods exposed at the objects.
  • 10. Static VS Dynamic Static/Dynamic typing is about when type information is aquired (Either at compile time or at runtime) Strong VS Weak Strong/Weak typing is about how strictly types are distinguished (e.g. whether the language tries to do implicit conversion from strings to numbers). PHP => Dynamic & Weak Ruby => Dynamic & Strong Java =>Static & Strong
  • 12. Statically typed Purely functional Type inference Concurrent Lazy Packages Haskell
  • 13. Every expression in Haskell has a type which is determined at compile time. All the types composed together by function application have to match up. If they don't, the program will be rejected by the compiler. Types become not only a form of guarantee, but a language for expressing the construction of programs. Statically typed
  • 14. You don't have to explicitly write out every type in a Haskell program. Types will be inferred by unifying every type bidirectionally. However, you can write out types if you choose, or ask the compiler to write them for you for handy documentation. Type inference
  • 15. Every function in Haskell is a function in the mathematical sense (i.e., "pure"). Even side-effecting IO operations are but a description of what to do, produced by pure code. There are no statements or instructions, only expressions which cannot mutate variables (local or global) nor access state like time or random numbers. Purely functional
  • 16. Haskell lends itself well to concurrent programming due to its explicit handling of effects. Its flagship compiler, GHC, comes with a high-performance parallel garbage collector and light-weight concurrency library containing a number of useful concurrency primitives and abstractions. Concurrent
  • 17. Functions don't evaluate their arguments. This means that programs can compose together very well, with the ability to write control constructs (such as if/else) just by writing normal functions. The purity of Haskell code makes it easy to fuse chains of functions together, allowing for performance benefits. Lazy
  • 18. Haskell Resources Haskell Website Haskell by Example Haskell Wiki Haskell for all School of Haskell
  • 19. Scala General purpose programming language Multi-paradigm language (functional & object oriented) Very strong static type system Very rich language Compiled language Run in JVM Can use any java package inside it directly 2003
  • 23. Erlang First release 1986, in Ericsson Company While threads require external library support in most languages, Erlang provides language-level features for creating and managing processes with the aim of simplifying concurrent programming. Though all concurrency is explicit in Erlang, processes communicate using message passing instead of shared variables, which removes the need for explicit locks (a locking scheme is still used internally by the VM) Why Erlang => http://veldstra.org/whyerlang/
  • 24. Thread VS Process 1. Threads are easier to create than processes since they don't require a separate address space. 2. Multithreading requires careful programming since threads share data structures that should only be modified by one thread at a time. Unlike threads, processes don't share the same address space. 3. Threads are considered lightweight because they use far less resources than processes. 4. Processes are independent of each other. Threads, since they share the same address space are interdependent, so caution must be taken so that different threads don't step on each other. This is really another way of stating #2 above. 5. A process can consist of multiple threads.
  • 25. Erlang handle very large number of concurrent activities be easily distributable over a network of computers be fault-tolerant to both software & hardware errors scale with the number of machines on the network be upgradeable & reconfigurable without having to stop & restart be responsive to users within certain strict timeframes stay in continuous operation for many years
  • 28. Database Trend 1. BigData and Hadoop a. MapReduce 2. NoSql Databases a. Cassandra b. MongoDB c. RethinkDB 3. Full Text Search a. ElasticSearch
  • 29. Column Oriented Database A column-oriented DBMS is a database management system (DBMS) that stores data tables as sections of columns of data rather than as rows of data. In comparison, most relational DBMSs store data in rows. This column-oriented DBMS has advantages for data warehouses, clinical data analysis, customer relationship management (CRM) systems, and library card catalogs, and other ad hoc inquiry systems where aggregates are computed over large numbers of similar data items.
  • 30. Cassandra Massively scalable partitioned row store masterless architecture linear scale performance no single points of failure read/write support across multiple datacenters & cloud availability zones. API / Query Method: CQL and Thrift, replication: peer-to-peer, written in: Java, Concurrency: tunable consistency built-in data compression MapReduce support, primary/secondary indexes
  • 31. Cassandra Decentralized Every node in the cluster has the same role. There is no single point of failure. Data is distributed across the cluster (so each node contains different data), but there is no master as every node can service any request. Supports replication and multi datacenter replication Replication strategies are configurable. Cassandra is designed as a distributed system, for deployment of large numbers of nodes across multiple data centers. Key features of Cassandra’s distributed architecture are specifically tailored for multiple-data center deployment, for redundancy, for failover and disaster recovery. Scalability Read and write throughput both increase linearly as new machines are added, with no downtime or interruption to applications. Fault-tolerant Data is automatically replicated to multiple nodes for fault-tolerance. Replication across multiple data centers is supported. Failed nodes can be replaced with no downtime.
  • 32. Cassandra Tunable consistency Writes and reads offer a tunable level of consistency, all the way from "writes never fail" to "block for all replicas to be readable", with the quorum level in the middle MapReduce support Cassandra has Hadoop integration, with MapReduce support. There is support also for Apache Pig and Apache Hive. Query language Cassandra introduces CQL (Cassandra Query Language), a SQL-like alternative to the traditional RPC interface. CQL is simple API meant for accessing Cassandra.
  • 33. ReThinkDB NoSql for real time web applications. Powerful query language Very easy UI Scale in seconds (r.table('games').reconfigure(shards=5, replicas=3)) Suitable for Web + mobile apps Multiplayer games Real time marketplaces
  • 34. Tools Docker Vagrant Sass / Less Gulp / Grant Ansible / chef / Puppet Jenkins Zmq / RabbitMq / Kafka
  • 36. Extra Steps Read => Read =>Read=>...... More Knowledge more powerful More Knowledge more productive Follow developers in github Read others source code Answers questions in Stackoverflow subscribe to any learning source packtpub