(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
Whether you're trying to give back to the open source community or collaborating on your own projects, knowing how to properly fork and generate pull requests is essential. Unfortunately, it's quite easy to make mistakes or not know what you should do when you're initially learning the process. I know that I certainly had considerable initial trouble with it, and I found a lot of the information on GitHub and around the internet to be rather piecemeal and incomplete - part of the process described here, another there, common hangups in a different place, and so on.
In an attempt to coallate this information for myself and others, this short tutorial is what I've found to be fairly standard procedure for creating a fork, doing your work, issuing a pull request, and merging that pull request back into the original project.
Just head over to the GitHub page and click the "Fork" button. It's just that simple. Once you've done that, you can use your favorite git client to clone your repo or j
// need to add the Apache WS XMLSchema library to spark/jars (does not have dependencies) | |
// https://repo1.maven.org/maven2/org/apache/ws/xmlschema/xmlschema-core/2.2.5/xmlschema-core-2.2.5.jar | |
import org.apache.ws.commons.schema.XmlSchemaCollection | |
import java.io.StringReader | |
import scala.collection.JavaConverters._ | |
import org.apache.ws.commons.schema._ | |
import org.apache.ws.commons.schema.constants.Constants | |
import org.apache.spark.sql.types._ |
This is a guide for Scala and Java development on Windows, using Windows Subsystem for Linux, although a bunch of it is applicable to a VirtualBox / Vagrant / Docker subsystem environment. This is not complete, but is intended to be as step by step as possible.
Read the entire Decent Security guide, and follow the instructions, especially:
Kafka acts as a kind of write-ahead log (WAL) that records messages to a persistent store (disk) and allows subscribers to read and apply these changes to their own stores in a system appropriate time-frame.
Terminology:
/* | |
Usage: you'll want to search for the strings <bucket> and <prefix>, and insert the S3 bucket where your access | |
logs are being delivered. Use (or delete) <prefix> to filter to a subset of your logs. | |
*/ | |
/* | |
These commented out configuration settings you can either run yourself in the REPL and source this file using | |
`.read parse_s3_access_logs.sql`, or you can uncomment them and supply values for yourself. |
mix3d asked for some help using this guide with windows so here we go. This was tested with Windows 10. Run all commands in Git Bash once it's installed.
Github will be the main account and bitbucket the secondary.
package fpmax | |
import scala.util.Try | |
import scala.io.StdIn.readLine | |
object App0 { | |
def main: Unit = { | |
println("What is your name?") | |
val name = readLine() |
# coding: utf-8 | |
import os | |
from azure.storage.blob import BlobServiceClient | |
class DownloadADLS: | |
def __init__(self, connection_string, container_name): | |
service_client = BlobServiceClient.from_connection_string(connection_string) | |
self.client = service_client.get_container_client(container_name) | |
#!groovy | |
# Best of Jenkinsfile | |
# `Jenkinsfile` is a groovy script DSL for defining CI/CD workflows for Jenkins | |
node { | |
} |