In this talk, I spoke about parallelism and concurrency and how you can achieve the same behavioral pattern you can achieve with Node.js using await/async statements, using goroutines and channels with Golang.
The document discusses writing concurrent programs robustly using Go and zeromq. Go has concurrency built into the language using goroutines and channels, avoiding the need for external libraries. Zeromq is a networking library that can be used from Go programs to allow concurrent processes to communicate across machines using patterns like publish/subscribe. An example program shows how Go and zeromq can be used together to build a concurrent and fault-tolerant application for moving data between processes.
Go is a language developed by Google with multi-core in mind. Differ from other languages, concurrency is a first-class primitive in Go. This talk covers some useful patterns for dealing with concurrency.
Kotlin Coroutines Flow is coming to provide a cold asynchronous data stream that emits values sequentially within a coroutine. Flow allows mapping, filtering, and collecting values, handles exceptions transparently, and preserves context. It can integrate with existing APIs like Room and Retrofit using adapters, and is the primary way to handle async streams going forward. Channels will still be used for hot streams and synchronization between coroutines.
Go uses goroutines and channels for concurrency. Goroutines are lightweight threads that communicate through channels, which are typed queues that allow synchronous message passing. Channels can be used to synchronize access to shared memory, allowing both shared memory and message passing for concurrency. The language is designed for scalable fine-grained concurrency but further improvements are still needed, especially to the goroutine scheduler.
This document discusses concurrency in Go and provides examples of using goroutines and channels for common concurrency patterns like background jobs, streaming data processing, and building services. It explains how goroutines allow running functions concurrently, and how typed channels enable goroutines to communicate and synchronize work through message passing. The examples demonstrate spawning goroutines, piping data between processes, and implementing a service backend that handles requests concurrently using a select statement.
This document introduces John Vlachoyiannis and discusses live programming of music using Clojure. It outlines how Clojure allows music to be treated as data that can be manipulated and transformed in real time. Examples are given showing how to define notes and samples as data, generate patterns, and manipulate those patterns by reversing, randomizing, or applying other transformations to the music structure. Live programming is enabled through use of the REPL and functions like play! that allow musical experiments to be conducted and heard immediately.
The document discusses Kotlin coroutines and how they can be used to write asynchronous code in a synchronous, sequential way. It explains what coroutines are, how they work internally using continuation-passing style (CPS) transformation and state machines, and compares them to callbacks. It also outlines some of the benefits of using coroutines, such as structured concurrency, light weight execution, built-in cancellation, and simplifying asynchronous code. Finally, it provides examples of how to use common coroutine builders like launch, async, and coroutineScope in a basic Android application with ViewModels.
The document discusses how the Go runtime handles network namespaces when using Docker and how Go version 1.10 addressed issues with incorrect interface information detected by goroutines. Specifically, it notes that in earlier versions, goroutines could inherit incorrect interface state from already running threads, but Go 1.10 introduced template threads to isolate goroutines and ensure each starts with a clean network namespace state. The document provides examples of the runtime behavior before and after 1.10 and recommends using Go 1.10 or higher when creating and managing Linux network namespaces.
The document discusses writing concurrent programs robustly using Go and zeromq. Go has concurrency built into the language using goroutines and channels, avoiding the need for external libraries. Zeromq is a networking library that can be used from Go programs to allow concurrent processes to communicate across machines using patterns like publish/subscribe. An example program shows how Go and zeromq can be used together to build a concurrent and fault-tolerant application for moving data between processes.
Go is a language developed by Google with multi-core in mind. Differ from other languages, concurrency is a first-class primitive in Go. This talk covers some useful patterns for dealing with concurrency.
Kotlin Coroutines Flow is coming to provide a cold asynchronous data stream that emits values sequentially within a coroutine. Flow allows mapping, filtering, and collecting values, handles exceptions transparently, and preserves context. It can integrate with existing APIs like Room and Retrofit using adapters, and is the primary way to handle async streams going forward. Channels will still be used for hot streams and synchronization between coroutines.
Go uses goroutines and channels for concurrency. Goroutines are lightweight threads that communicate through channels, which are typed queues that allow synchronous message passing. Channels can be used to synchronize access to shared memory, allowing both shared memory and message passing for concurrency. The language is designed for scalable fine-grained concurrency but further improvements are still needed, especially to the goroutine scheduler.
This document discusses concurrency in Go and provides examples of using goroutines and channels for common concurrency patterns like background jobs, streaming data processing, and building services. It explains how goroutines allow running functions concurrently, and how typed channels enable goroutines to communicate and synchronize work through message passing. The examples demonstrate spawning goroutines, piping data between processes, and implementing a service backend that handles requests concurrently using a select statement.
This document introduces John Vlachoyiannis and discusses live programming of music using Clojure. It outlines how Clojure allows music to be treated as data that can be manipulated and transformed in real time. Examples are given showing how to define notes and samples as data, generate patterns, and manipulate those patterns by reversing, randomizing, or applying other transformations to the music structure. Live programming is enabled through use of the REPL and functions like play! that allow musical experiments to be conducted and heard immediately.
The document discusses Kotlin coroutines and how they can be used to write asynchronous code in a synchronous, sequential way. It explains what coroutines are, how they work internally using continuation-passing style (CPS) transformation and state machines, and compares them to callbacks. It also outlines some of the benefits of using coroutines, such as structured concurrency, light weight execution, built-in cancellation, and simplifying asynchronous code. Finally, it provides examples of how to use common coroutine builders like launch, async, and coroutineScope in a basic Android application with ViewModels.
The document discusses how the Go runtime handles network namespaces when using Docker and how Go version 1.10 addressed issues with incorrect interface information detected by goroutines. Specifically, it notes that in earlier versions, goroutines could inherit incorrect interface state from already running threads, but Go 1.10 introduced template threads to isolate goroutines and ensure each starts with a clean network namespace state. The document provides examples of the runtime behavior before and after 1.10 and recommends using Go 1.10 or higher when creating and managing Linux network namespaces.
Puppet User Group Presentation - 15 March 2012Walter Heck
The document discusses a puppet user group meeting in Kuala Lumpur, Malaysia. It introduces OlinData, a company that provides Puppet consulting and training services, and discusses how Puppet can help automate server configuration management compared to manual methods. Future plans are outlined for Puppet training in Southeast Asia through OlinData and an upcoming Puppet user group meetup.
Goal of this talk is to get through performance analysis process of simple calculator application implemented as a set of microservices with following FOSS toolset: k6 and gatling for traffic generation, prometheus for monitoring, perf Linux profiler and FlameGraph project for flame graphs generation.
This document discusses setting up a GRE overlay network to create a distributed switch. It outlines creating GRE tunnels between endpoints, disabling NetworkManager, configuring interfaces and bridges, populating the routing table, allowing GRE traffic through the firewall, and testing connectivity. Troubleshooting steps include checking interfaces, IP addresses, routing tables, and firewall rules.
The document discusses building a concurrent events collector microservice in Go. It describes collecting events from clients over HTTP, buffering them, and passing batches to a processor. It presents three versions of the collector: (1) a naive synchronous approach, (2) an improved concurrent version using worker goroutines, and (3) a final version that forces flushing buffers periodically using a timer. The final collector implementation provides good concurrency while avoiding blocking the collection of new events.
This document summarizes a presentation about coding in the Go programming language. It discusses:
- A brief history of Go and how it was created at Google in 2007.
- What makes Go special, including its fast compilation, lack of a virtual machine, concurrency features using goroutines and channels, and standard library.
- An overview of Go's syntax including variables, loops, conditions, arrays, maps, functions, closures, pointers, and structs.
- How to handle concurrency using goroutines and channels.
- Building HTTP servers and APIs in Go using the net/http package.
- Popular Go frameworks and toolkits like Gorilla Mux
A presentation about combining the powers of the Go language and Asterisk in order to provide fast, reliable and hugely scalable voice applications. A brief introduction about why Go presents a big opportunity for the asterisk community, a primer into developing FastAGI applications, demonstration of the AGI package [1] and a walk through the idioms and challenges of developing in Go. The talk is focused mainly on our experience of porting existing code into Go with the aim to scale our services to larger numbers accompanied with benchmarks and an introduction to some tools [2] we developed to help us test, debug and benchmark AGI applications.
Golang and GoatCore were created to build web applications. The document provides steps to set up a development environment for Go and GoatCore, including installing dependencies like Mingw, Go, Git, Atom, and Postgres. It also demonstrates building and running a GoatCore project, and discusses features of Go like concurrency using channels and the runtime. GoatCore provides internationalization support and performs efficient JSON parsing by operating on byte-level payloads.
This document discusses concurrency and parallelism. It defines concurrency as dealing with multiple things at once through structuring solutions, while defining parallelism as doing multiple things at once through execution. It provides examples of concurrency concepts in Go including goroutines, channels, and the Go scheduler. It also gives best practices for concurrency in Go such as using wait groups, channels, contexts, and message queues.
This document describes how to import and analyze GitHub event data stored in JSON files using the Neo4j graph database. It provides examples of Cypher queries that can be used to analyze relationships between users, repositories, pull requests, forks and other GitHub elements from the events data. These include queries to find the most active user, most forked repository, number of comments on pull requests before being merged, and users who have worked on the same repositories through merged pull requests.
Cotap Tech Talks: Keith Lazuka, Digital Communication using Sound and SwiftEvan Owen
A brief talk about how audio systems can be used to exchange digital data. The emphasis will be on iOS devices using Apple's audio frameworks with code written in Swift.
Keith studied Russian language and literature in school. He then realized that all of the jobs are in computers. He started writing apps for iOS in 2008. He created a proximity-based mobile device pairing system using ultrasonic sound waves at Circle 38. Later, he went on to help build the Acompli app for iOS, which was acquired by Microsoft last year. Now, he’s working at Microsoft in SF on the Outlook iOS app.
This document provides an overview of basic commands and functions for constructing, sending, receiving, and analyzing packets using Scapy. It summarizes key Scapy commands for listing available protocols and functions, configuring parameters, building packets by specifying addresses, ports, and layer values, sending and receiving packets on different interfaces, capturing live packets, and fuzzing packet fields. The document is a quick reference for common Scapy tasks.
The document discusses various container data structures in Go, including lists, rings, heaps, maps, and slices. It provides code examples and explanations for each: lists are implemented as doubly-linked lists; rings provide a circular list; heaps implement min-heap trees; maps are unordered dictionaries; slices are references to arrays. Channels can also act as FIFO queues when buffered. The document advocates for some form of generics in Go to avoid type assertions.
Storm is an open-source distributed real-time computation system. It provides high-level abstractions like Trident for building scalable, fault-tolerant, data streaming applications. Storm guarantees processing of all input data through its distributed architecture of spouts, bolts, and streams. It allows for exactly-once processing semantics through ordered transactional topologies using Trident state management.
Go is a simple language with familiar syntax, but still, there are features, which implementation differs from most part of other programming languages. For example, the idea of CSP implemented as concurrency paradigm is used for parallelism in Go. It looks like a simple API, but under the hood, it is very complicated, but interesting mechanism. We will discuss, how it really works.
(Slides from the speech on Kharkiv Go meetup 14 Sep 2019)
Perl - laziness, impatience, hubris, and one linersKirk Kimmel
Perl provides tools like perldoc, cpan, and Perl::Tidy to help developers work more efficiently. One-liners allow running Perl commands and programs directly from the command line. ExtUtils::Command provides functions that emulate common shell commands to make Perl scripts more portable. Perl::Tidy can reformat code to make it more readable.
This document discusses designing for concurrency in Golang. It provides two examples of concurrent systems and how they can be modeled using Goroutines. Goroutines are lightweight threads that allow implementing one goroutine per concurrent activity. This approach avoids sharing memory and uses message passing with channels for communication. The document concludes that Goroutines are cheap to create and fast to schedule, enabling designs that don't share memory and have many concurrent Goroutines. Code samples and references for further reading on Golang concurrency patterns are also provided.
This document provides a summary of ntpd configuration options for unicast and broadcast/multicast modes. It describes options for configuring time servers, peers, and polling intervals. It also outlines commands for ntpq, generating statistics, and the format of statistics files.
This document provides an overview of the Go programming language including:
- A brief history of Go from its origins at Google in 2007 to current widespread usage.
- Key features of Go like functions, structs, interfaces, methods, slices, pointers, go-routines and channels.
- Examples of basic Go code demonstrating functions, structs, methods, interfaces, concurrency with go-routines and channels.
- Discussion of things missing from Go like classes, generics and exceptions.
- Quotes from developers commenting both positively and negatively on Go's simplicity and tradeoffs.
- Links to further resources like the Go tour to learn more.
Conférence des Geeks Anonymes sur " le langage Go ", par Thomas Hayen le 23 septembre 2020.
Cette conférence est disponible en vidéo sur Youtube : https://youtu.be/AlGGneVGTJk
Puppet User Group Presentation - 15 March 2012Walter Heck
The document discusses a puppet user group meeting in Kuala Lumpur, Malaysia. It introduces OlinData, a company that provides Puppet consulting and training services, and discusses how Puppet can help automate server configuration management compared to manual methods. Future plans are outlined for Puppet training in Southeast Asia through OlinData and an upcoming Puppet user group meetup.
Goal of this talk is to get through performance analysis process of simple calculator application implemented as a set of microservices with following FOSS toolset: k6 and gatling for traffic generation, prometheus for monitoring, perf Linux profiler and FlameGraph project for flame graphs generation.
This document discusses setting up a GRE overlay network to create a distributed switch. It outlines creating GRE tunnels between endpoints, disabling NetworkManager, configuring interfaces and bridges, populating the routing table, allowing GRE traffic through the firewall, and testing connectivity. Troubleshooting steps include checking interfaces, IP addresses, routing tables, and firewall rules.
The document discusses building a concurrent events collector microservice in Go. It describes collecting events from clients over HTTP, buffering them, and passing batches to a processor. It presents three versions of the collector: (1) a naive synchronous approach, (2) an improved concurrent version using worker goroutines, and (3) a final version that forces flushing buffers periodically using a timer. The final collector implementation provides good concurrency while avoiding blocking the collection of new events.
This document summarizes a presentation about coding in the Go programming language. It discusses:
- A brief history of Go and how it was created at Google in 2007.
- What makes Go special, including its fast compilation, lack of a virtual machine, concurrency features using goroutines and channels, and standard library.
- An overview of Go's syntax including variables, loops, conditions, arrays, maps, functions, closures, pointers, and structs.
- How to handle concurrency using goroutines and channels.
- Building HTTP servers and APIs in Go using the net/http package.
- Popular Go frameworks and toolkits like Gorilla Mux
A presentation about combining the powers of the Go language and Asterisk in order to provide fast, reliable and hugely scalable voice applications. A brief introduction about why Go presents a big opportunity for the asterisk community, a primer into developing FastAGI applications, demonstration of the AGI package [1] and a walk through the idioms and challenges of developing in Go. The talk is focused mainly on our experience of porting existing code into Go with the aim to scale our services to larger numbers accompanied with benchmarks and an introduction to some tools [2] we developed to help us test, debug and benchmark AGI applications.
Golang and GoatCore were created to build web applications. The document provides steps to set up a development environment for Go and GoatCore, including installing dependencies like Mingw, Go, Git, Atom, and Postgres. It also demonstrates building and running a GoatCore project, and discusses features of Go like concurrency using channels and the runtime. GoatCore provides internationalization support and performs efficient JSON parsing by operating on byte-level payloads.
This document discusses concurrency and parallelism. It defines concurrency as dealing with multiple things at once through structuring solutions, while defining parallelism as doing multiple things at once through execution. It provides examples of concurrency concepts in Go including goroutines, channels, and the Go scheduler. It also gives best practices for concurrency in Go such as using wait groups, channels, contexts, and message queues.
This document describes how to import and analyze GitHub event data stored in JSON files using the Neo4j graph database. It provides examples of Cypher queries that can be used to analyze relationships between users, repositories, pull requests, forks and other GitHub elements from the events data. These include queries to find the most active user, most forked repository, number of comments on pull requests before being merged, and users who have worked on the same repositories through merged pull requests.
Cotap Tech Talks: Keith Lazuka, Digital Communication using Sound and SwiftEvan Owen
A brief talk about how audio systems can be used to exchange digital data. The emphasis will be on iOS devices using Apple's audio frameworks with code written in Swift.
Keith studied Russian language and literature in school. He then realized that all of the jobs are in computers. He started writing apps for iOS in 2008. He created a proximity-based mobile device pairing system using ultrasonic sound waves at Circle 38. Later, he went on to help build the Acompli app for iOS, which was acquired by Microsoft last year. Now, he’s working at Microsoft in SF on the Outlook iOS app.
This document provides an overview of basic commands and functions for constructing, sending, receiving, and analyzing packets using Scapy. It summarizes key Scapy commands for listing available protocols and functions, configuring parameters, building packets by specifying addresses, ports, and layer values, sending and receiving packets on different interfaces, capturing live packets, and fuzzing packet fields. The document is a quick reference for common Scapy tasks.
The document discusses various container data structures in Go, including lists, rings, heaps, maps, and slices. It provides code examples and explanations for each: lists are implemented as doubly-linked lists; rings provide a circular list; heaps implement min-heap trees; maps are unordered dictionaries; slices are references to arrays. Channels can also act as FIFO queues when buffered. The document advocates for some form of generics in Go to avoid type assertions.
Storm is an open-source distributed real-time computation system. It provides high-level abstractions like Trident for building scalable, fault-tolerant, data streaming applications. Storm guarantees processing of all input data through its distributed architecture of spouts, bolts, and streams. It allows for exactly-once processing semantics through ordered transactional topologies using Trident state management.
Go is a simple language with familiar syntax, but still, there are features, which implementation differs from most part of other programming languages. For example, the idea of CSP implemented as concurrency paradigm is used for parallelism in Go. It looks like a simple API, but under the hood, it is very complicated, but interesting mechanism. We will discuss, how it really works.
(Slides from the speech on Kharkiv Go meetup 14 Sep 2019)
Perl - laziness, impatience, hubris, and one linersKirk Kimmel
Perl provides tools like perldoc, cpan, and Perl::Tidy to help developers work more efficiently. One-liners allow running Perl commands and programs directly from the command line. ExtUtils::Command provides functions that emulate common shell commands to make Perl scripts more portable. Perl::Tidy can reformat code to make it more readable.
This document discusses designing for concurrency in Golang. It provides two examples of concurrent systems and how they can be modeled using Goroutines. Goroutines are lightweight threads that allow implementing one goroutine per concurrent activity. This approach avoids sharing memory and uses message passing with channels for communication. The document concludes that Goroutines are cheap to create and fast to schedule, enabling designs that don't share memory and have many concurrent Goroutines. Code samples and references for further reading on Golang concurrency patterns are also provided.
This document provides a summary of ntpd configuration options for unicast and broadcast/multicast modes. It describes options for configuring time servers, peers, and polling intervals. It also outlines commands for ntpq, generating statistics, and the format of statistics files.
This document provides an overview of the Go programming language including:
- A brief history of Go from its origins at Google in 2007 to current widespread usage.
- Key features of Go like functions, structs, interfaces, methods, slices, pointers, go-routines and channels.
- Examples of basic Go code demonstrating functions, structs, methods, interfaces, concurrency with go-routines and channels.
- Discussion of things missing from Go like classes, generics and exceptions.
- Quotes from developers commenting both positively and negatively on Go's simplicity and tradeoffs.
- Links to further resources like the Go tour to learn more.
Conférence des Geeks Anonymes sur " le langage Go ", par Thomas Hayen le 23 septembre 2020.
Cette conférence est disponible en vidéo sur Youtube : https://youtu.be/AlGGneVGTJk
The Ring programming language version 1.7 book - Part 82 of 196Mahmoud Samir Fayed
This document provides information about distributing Ring applications using the Ring2EXE tool. Ring2EXE can generate executable files for Windows, Linux, macOS, and mobile devices from Ring source code. It works by first compiling the Ring code to a Ring object file, then embedding that object file into a C program along with the Ring runtime library to generate an executable. Options allow controlling library inclusion and target platform. Examples demonstrate building console, GUI, game, and mobile applications using Ring2EXE.
Go is a statically typed, compiled programming language designed at Google in 2007 to improve programming productivity for multicore and networked machines. It addresses criticisms of other languages used at Google while keeping useful characteristics like C's performance, Python's readability, and support for high-performance networking and multiprocessing. Go is syntactically similar to C but adds memory safety, garbage collection, and CSP-style concurrency. There are two major implementations that target multiple platforms including WebAssembly. Go aims to guarantee that code written for one version will continue to build and run with future versions.
httplinux.die.netman3execfork() creates a new process by.docxadampcarr67227
http://linux.die.net/man/3/exec
fork() creates a new process by duplicating the calling process. The new process, referred to as the child, is an exact duplicate of the calling process, referred to as the parent#include <unistd.h>pid_t fork(void);
The exec() family of functions replaces the current process image with a new process image. The functions described in this manual page are front-ends for execve(2). (See the manual page for execve(2) for further details about the replacement of the current process image.)
The exec() family of functions include execl, execlp, execle, execv, execvp, and execvpe to execute a file.
The ANSI prototype for execl() is:
int execl(const char *path, const char *arg0,..., const char *argn, 0)
http://www.cems.uwe.ac.uk/~irjohnso/coursenotes/lrc/system/pc/pc4.htm #inciude <stdio.h> #inciude <unistd.h> main() { execl("/bin/ls", "ls", "-l", 0); printf("Can only get here on error\n"); }
The first parameter to execl() in this example is the full pathname to the ls command. This is the file whose contents will be run, provided the process has execute permission on the file. The rest of the execl() parameters provide the strings to which the argv array elements in the new program will point. In this example, it means that the ls program will see the string ls pointed to by its argv[0], and the string -l pointed to by itsargv[1]. In addition to making all these parameters available to the new program, the exec() calls also pass a value for the variable: extern char **environ;
This variable has the same format as the argv variable except that the items passed via environ are the values in the environment of the process (like any exported shell variables), rather than the command line parameters. In the case of execl(), the value of the environ variable in the new program will be a copy of the value of this variable in the calling process.
The execl() version of exec() is fine in the circumstances where you can ex-plicitly list all of the parameters, as in the previous example. Now suppose you want to write a program that doesn't just run ls, but will run any program you wish, and pass it any number of appropriate command line parameters. Obviously, execl() won't do the job.
The example program below, which implements this requirement, shows, however, that the system call execv() will perform as required: #inciude <stdio.h> main(int argc, char **argv) { if (argc==1) { printf("Usage: run <command> [<paraneters>]\n"); exit(1) } execv(argv[l], &argv[1)); printf("Sorry... couldn't run that!\n"); }
The prototype for execv() shows that it only takes two parameters, the first is the full pathname to the command to execute and the second is the argv value you want to pass into the new program. In the previous example this value was derived from the argv value passed into the run command, so that the run command can take the command line parameter values you pass it and just pass them on. int execl(.
The document outlines the schedule and objectives for an operating systems lab course over 10 weeks. The first few weeks focus on writing programs using Unix system calls like fork, exec, wait. Later weeks involve implementing I/O system calls, simulating commands like ls and grep, and scheduling algorithms like FCFS, SJF, priority and round robin. Students are asked to display Gantt charts, compute waiting times and turnaround times for each algorithm. The final weeks cover inter-process communication, the producer-consumer problem, and memory management techniques.
Talk Python To Me: Stream Processing in your favourite Language with Beam on ...Aljoscha Krettek
Flink is a great stream processor, Python is a great programming language, Apache Beam is a great programming model and portability layer. Using all three together is a great idea! We will demo and discuss writing Beam Python pipelines and running them on Flink. We will cover Beam's portability vision that led here, what you need to know about how Beam Python pipelines are executed on Flink, and where Beam's portability framework is headed next (hint: Python pipelines reading from non-Python connectors)
Help Needed!UNIX Shell and History Feature This project consists.pdfmohdjakirfb
Help Needed!
UNIX Shell and History Feature
This project consists of designing a C program to serve as a shell interface
that accepts user commands and then executes each command in a separate
process. This project can be completed on any Linux,
UNIX,orMacOS X system.
A shell interface gives the user a prompt, after which the next command
is entered. The example below illustrates the prompt
osh> and the user’s
next command:
cat prog.c. (This command displays the le prog.c on the
terminal using the
UNIX cat command.)
osh> cat prog.c
One technique for implementing a shell interface is to have the parent process
rst read what the user enters on the command line (in this case,
cat
prog.c), and then create a separate child process that performs the command.
Unless otherwise specied, the parent process waits for the child to exit
before continuing. This is similar in functionality to the new process creation
illustrated in Figure 3.10. However,
UNIX shells typically also allow the child
process to run in the background, or concurrently. To accomplish this, we add
an ampersand (&) at the end of the command. Thus, if we rewrite the above
command as
osh> cat prog.c &
the parent and child processes will run concurrently.
The separate child process is created using the
fork() system call, and the
user’s command is executed using one of the system calls in the
exec() family
A C program that provides the general operations of a command-line shell
is supplied in Figure 3.36. The
main() function presents the prompt osh->
and outlines the steps to be taken after input from the user has been read. The
main() function continually loops as long as should run equals 1; when the
user enters
exit at the prompt, your program will set should run to 0 and
terminate.
This project is organized into two parts: (1) creating the child process and
executing the command in the child, and (2) modifying the shell to allow a
history feature.
#include
#include
#define MAXLINE 80 /* The maximum length command */
int main(void)
{
char *args[MAXLINE/2 + 1]; /* command line arguments */
int should
run = 1; /* flag to determine when to exit program */
while (should run) {
printf(\"osh>\");
}
fflush(stdout);
/**
* After reading user input, the steps are:
* (1) fork a child process using fork()
* (2) the child process will invoke execvp()
* (3) if command included &, parent will invoke wait()
*/
return 0;
}
Part I — Creating a Child Process
The rst task is to modify the
main() function in the above program so that a child
process is forked and executes the command specied by the user. This will
require parsing what the user has entered into separate tokens and storing the
tokens in an array of character strings (
args in the above program. For example, if the
user enters the command
ps -ael at the osh> prompt, the values stored in the
args array are:
args[0] = \"ps\"
args[1] = \"-ael\"
args[2] = NULL
This args array will be passed to the execvp() function, which has the
following prot.
These are the slides for the seminar to have a basic overview on the GO Language, By Alessandro Sanino.
They were used on a Lesson in University of Turin (Computer Science Department) 11-06-2018
This document discusses implementing a job queue in Golang. It begins by explaining buffered and unbuffered channels, and shows examples of using channels to coordinate goroutines. It then demonstrates how to build a job queue that uses a channel to enqueue jobs and have worker goroutines process jobs from the channel concurrently. It also discusses ways to gracefully shutdown workers using contexts and wait groups. Finally, it covers topics like auto-scaling agents, communicating between servers and agents, and handling job cancellation.
Pablo Magaz | ECMAScript 2018 y más allá | Codemotion Madrid 2018Codemotion
The document summarizes upcoming features in ECMAScript beyond 2018. It discusses proposals that are in stage 0-3 of the standardization process, including array flat and flatMap, dynamic imports, private fields and methods, and observable objects. It also outlines more experimental proposals in earlier stages, like top level await, pipeline operators, and regular expression improvements like named capture groups and lookbehind assertions. The talk provides examples to demonstrate many of these new language features and how they may be used.
Flink Forward Berlin 2017: Aljoscha Krettek - Talk Python to me: Stream Proce...Flink Forward
Flink is a great stream processor, Python is a great programming language, Apache Beam is a great programming model and portability layer. Using all three together is a great idea! We will demo and discuss writing Beam Python pipelines and running them on Flink. We will cover Beam's portability vision that led here, what you need to know about how Beam Python pipelines are executed on Flink, and where Beam's portability framework is headed next (hint: Python pipelines reading from non-Python connectors)
The async/await paradigm is implemented in a variety of different popular programming languages, but it is not the same thing everywhere.
In this presentation I'll show you an overview of the basic asyncrounous programming in Rust "flavor".
We will se the why the community had decided to introduce this paradigm, and how it has matched some critical aspects with the Rust philosophy.
Golang basics for Java developers - Part 1Robert Stern
This document provides an overview of Golang basics for Java developers. It covers Golang's history, features, syntax, data types, flow control, functions and interfaces, concurrency, and differences from Java. Key points include Golang being a compiled, statically typed language created at Google in 2007, its use of packages and imports, basic types like strings and integers, slices for dynamic arrays, maps for key-value pairs, functions with receivers, errors instead of exceptions, and goroutines for concurrency with channels.
This document provides an introduction and overview of MPI (Message Passing Interface). It discusses:
- MPI is a standard for message passing parallel programming that allows processes to communicate in distributed memory systems.
- MPI programs use function calls to perform all operations. Basic definitions are included in mpi.h header file.
- The basic model in MPI includes communicators, groups, and ranks to identify processes. MPI_COMM_WORLD identifies all processes.
- Sample MPI programs are provided to demonstrate point-to-point communication, collective communication, and matrix multiplication using multiple processes.
- Classification of common MPI functions like initialization, communication, and information queries are discussed.
This document provides an introduction and overview of the Go programming language. It discusses key Go concepts like concurrency using goroutines and channels, object-oriented programming using structs and interfaces, and real-world examples of Go in production systems. The document covers Go's simplicity, concurrency features, interfaces, and how these properties make Go well-suited for building scalable and performant web applications. It also provides performance comparisons between Ruby and Go implementations for common tasks.
This document provides an overview of message passing computing and the Message Passing Interface (MPI) library. It discusses message passing concepts, the Single Program Multiple Data (SPMD) model, point-to-point communication using send and receive routines, message tags, communicators, debugging tools, and evaluating performance through timing. Key points covered include how MPI defines a standard for message passing between processes, common routines like MPI_Send and MPI_Recv, and how to compile and execute MPI programs on multiple computers.
Vapor – Swift is not only for iOS anymoreMilan Vít
Slides from talk I have as part of Vapor Meetup 2 in Tokyo on 2018-07-06.
The video recording from this talk is available on YouTube (https://www.youtube.com/watch?v=Uq1fJifXcOc) but unfortunately, audio issues plagued my talk. At the very least, here are slides from that evening.
**Watch the full webinar at https://codefresh.io/events/terraform-gitops-codefresh/
Today we write "Infrastructure as Code" and even "Pipelines as Code", so let's start treating our "code as code" and practice CI/CD with GitOps! In this talk, we'll show you how we build and deploy applications with Terraform using GitOps and Codefresh. Cloud Posse is a Terraform power user that has developed over 130 Terraform modules which are free and open source. We'll share how we handle automation with security while making the process easy for engineers.
Similar to The async/await concurrency pattern in Golang (20)
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Discover the power of Cloud-Based IVR Solutions to streamline communication processes. Embrace scalability and cost-efficiency while enhancing customer experiences with features like automated call routing and voice recognition. Accessible from anywhere, these solutions integrate seamlessly with existing systems, providing real-time analytics for continuous improvement. Revolutionize your communication strategy today with Cloud-Based IVR Solutions. Learn more at: https://thesmspoint.com/channel/cloud-telephony
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Recording:
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AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI AppGoogle
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-fusion-buddy-review
AI Fusion Buddy Review: Key Features
✅Create Stunning AI App Suite Fully Powered By Google's Latest AI technology, Gemini
✅Use Gemini to Build high-converting Converting Sales Video Scripts, ad copies, Trending Articles, blogs, etc.100% unique!
✅Create Ultra-HD graphics with a single keyword or phrase that commands 10x eyeballs!
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✅With one keyword or URL, generate complete websites, landing pages, and more…
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See My Other Reviews Article:
(1) AI Genie Review: https://sumonreview.com/ai-genie-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
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These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
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- Invited for presentation at SoCal PLS ‘16.
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SQL has attained widespread adoption, but Business Intelligence tools still use their own higher level languages based upon a multidimensional paradigm. Composable calculations are what is missing from SQL, and we propose a new kind of column, called a measure, that attaches a calculation to a table. Like regular tables, tables with measures are composable and closed when used in queries.
SQL-with-measures has the power, conciseness and reusability of multidimensional languages but retains SQL semantics. Measure invocations can be expanded in place to simple, clear SQL.
To define the evaluation semantics for measures, we introduce context-sensitive expressions (a way to evaluate multidimensional expressions that is consistent with existing SQL semantics), a concept called evaluation context, and several operations for setting and modifying the evaluation context.
A talk at SIGMOD, June 9–15, 2024, Santiago, Chile
Authors: Julian Hyde (Google) and John Fremlin (Google)
https://doi.org/10.1145/3626246.3653374
4. Version 1.0
released
March, 2012
Go first appeared
in Google,
2007
November, 2009
Google announce Golang
to the worldwide
community
June, 2017
I released a
go-perceptron
on Github
Golang Developer Group
begins in Turin
January, 2020
2020
The community
grows!
19. package main
import "fmt"
func main() {
var a = "initial"
fmt.Println(a) # initial
var b, c int = 1, 2
fmt.Println(a, b) # 1, 2
var d = true
fmt.Println(d) # true
var e int
fmt.Println(e) # 0
f := "apple"
fmt.Println(f) # apple
}
22. Concurrency is the composition of independently
executing processes, while parallelism is the
simultaneous execution of (possibly related)
computations.
23. Introducing
goroutines
package main
import (
"fmt"
"time"
)
func f(from string) {
for i := 0; i < 3; i++ {
fmt.Println(from, ":", i)
}
}
func main() {
f("direct")
go f("goroutine")
go func(msg string) {
fmt.Println(msg)
}("going")
time.Sleep(time.Second)
fmt.Println("done")
}
24. Introducing
goroutines
package main
import (
"fmt"
"time"
)
func f(from string) {
for i := 0; i < 3; i++ {
fmt.Println(from, ":", i)
}
}
func main() {
f("direct")
go f("goroutine")
go func(msg string) {
fmt.Println(msg)
}("going")
time.Sleep(time.Second)
fmt.Println("done")
}
# standard function call
25. Introducing
goroutines
package main
import (
"fmt"
"time"
)
func f(from string) {
for i := 0; i < 3; i++ {
fmt.Println(from, ":", i)
}
}
func main() {
f("direct")
go f("goroutine")
go func(msg string) {
fmt.Println(msg)
}("going")
time.Sleep(time.Second)
fmt.Println("done")
}
# standard function call
# to invoke this function
in a goroutine, use go f(s).
This new goroutine will
execute concurrently with
the calling one.
26. When we run this program, we see
the output of the blocking call
first, then the interleaved output of
the two goroutines.
This interleaving reflects the
goroutines being run concurrently
by the Go runtime.
30. package main
import "fmt"
func main() {
messages := make(chan string)
go func() { messages <- "ping" }()
msg := <-messages
fmt.Println(msg)
}
# channels are typed by the
values they convey
Introducing
channels
31. package main
import "fmt"
func main() {
messages := make(chan string)
go func() { messages <- "ping" }()
msg := <-messages
fmt.Println(msg)
}
# channels are typed by the
values they convey
# when we run the program
the "ping" message is
successfully passed from one
goroutine to another via our
channel.
Introducing
channels
32. By default sends and receives block until
both the sender and receiver are ready.
This property allowed us to wait at the end
of our program for the "ping" message
without having to use any other
synchronization.
33. Philosophically, the idea behind Go is:
Don't communicate by sharing
memory; share memory by
communicating.
36. Promise
A promise is a special JavaScript
object that let links production and
consuming code
37. async
Before a function means “this function
always returns a Promise”
Promise
A promise is a special JavaScript
object that let links production and
consuming code
38. async
Before a function means “this function
always returns a Promise”
await
Works only inside async function and makes
JavaScript wait until that Promise settles
and returns its result
Promise
A promise is a special JavaScript
object that let links production and
consuming code
39. const sleep = require('util').promisify(setTimeout)
async function myAsyncFunction() {
await sleep(2000)
return 2
};
(async function() {
const result = await myAsyncFunction();
// outputs `2` after two seconds
console.log(result);
})();
40. // ... package main and imports
func myAsyncFunction() <-chan int32 {
r := make(chan int32)
go func() {
defer close(r)
// work to be completed
time.Sleep(time.Second * 2)
r <- 2
}()
return r
}
func main() {
r := <-myAsyncFunction()
// outputs `2` after two seconds
fmt.Println(r)
}
42. const myAsyncFunction = (s) => {
return new Promise((resolve) => {
setTimeout(() => resolve(s), 2000);
})
};
(async function() {
const result = await Promise.all([
myAsyncFunction(2),
myAsyncFunction(3)
]);
// outputs `2, 3` after two seconds
console.log(result);
})();
43. // ... package main and imports
func myAsyncFunction() <-chan int32 {
r := make(chan int32)
go func() {
defer close(r)
// work to be completed
time.Sleep(time.Second * 2)
r <- 2
}()
return r
}
func main() {
firstChannel, secondChannel :=
myAsyncFunction(2), myAsyncFunction(3)
first, second := <-firstChannel, <-secondChannel
// outputs `2, 3` after two seconds
fmt.Println(first, second)
}
44. The cool thing about channels is that
you can use Go's select statement
to implement concurrency patterns
and wait on multiple channel
operations.
46. const myAsyncFunction = (s) => {
return new Promise((resolve) => {
setTimeout(() => resolve(s), 2000);
})
};
(async function() {
const result = await Promise.race([
myAsyncFunction(2),
myAsyncFunction(3)
]);
// outputs `2` or `3` after two seconds
console.log(result);
})();
47. // ... package main and imports
func myAsyncFunction() <-chan int32 {
r := make(chan int32)
go func() {
defer close(r)
// work to be completed
time.Sleep(time.Second * 2)
r <- 2
}()
return r
}
func main() {
var r int32
select {
case r = <-myAsyncFunction(2)
case r = <-myAsyncFunction(3)
}
// outputs `2` or `3` after two seconds
fmt.Println(r)
}