littlecodersh

#coding=utf8
import itchat
# tuling plugin can be get here:
# https://github.com/littlecodersh/EasierLife/tree/master/Plugins/Tuling
from tuling import get_response

@itchat.msg_register('Text')
def text_reply(msg):
    if u'作者' in msg['Text'] or u'主人' in msg['Text']:
        return u'你可以在这里了解他：https://github.com/littlecodersh'

tomysmile

type below:

brew update
brew install redis

To have launchd start redis now and restart at login:

brew services start redis

jakubkulhan

import java.security.SecureRandom;

public class RandomString {
    private static final String ALPHABET = "0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ-_";
    private static final SecureRandom RANDOM = new SecureRandom();

    /**
     * Generates random string of given length from Base65 alphabet (numbers, lowercase letters, uppercase letters).
     *
     * @param count length

alopresto

#Steps to merge/close pull requests with two main branches

As NiFi now has a 1.0 (master) and 0.x (support) branch, pull requests (PR) must be applied to both. Here is a step-by-step guide for committers to ensure this occurs for all PRs. 

1. Check out the latest master
```	$ git checkout master
	$ git pull upstream master
```

2. Check out the PR (example #327). This will be in `detached-HEAD` state. (Note: You may need to edit the `.git/config` file to add the `fetch` lines [below](#fetch))

frgomes

// this flavour is pure magic...
def toDouble: (Any) => Double = { case i: Int => i case f: Float => f case d: Double => d }
  
// whilst this flavour is longer but you are in full control...
object any2Double extends Function[Any,Double] {
  def apply(any: Any): Double = 
    any match { case i: Int => i case f: Float => f case d: Double => d }
}

// like when you can invoke any2Double from another similar conversion...  

sadikovi

import org.apache.spark.sql.Row
import org.apache.spark.sql.expressions.{MutableAggregationBuffer, UserDefinedAggregateFunction}
import org.apache.spark.sql.types.{ArrayType, LongType, DataType, StructType, StructField}

class CollectionFunction(private val limit: Int) extends UserDefinedAggregateFunction {
    def inputSchema: StructType =
        StructType(StructField("value", LongType, false) :: Nil)

    def bufferSchema: StructType =
        StructType(StructField("list", ArrayType(LongType, true), true) :: Nil)

oza

YARN

1. General resource management layer on HDFS
2. A part of Hadoop

Spark

1. In memory processing framework

Spark on YARN

ololobus

Apache Spark installation + ipython/jupyter notebook integration guide for macOS

Tested with Apache Spark 2.1.0, Python 2.7.13 and Java 1.8.0_112

For older versions of Spark and ipython, please, see also previous version of text.

Install Java Development Kit

jkbradley

/*
This example uses Scala.  Please see the MLlib documentation for a Java example.

Try running this code in the Spark shell.  It may produce different topics each time (since LDA includes some randomization), but it should give topics similar to those listed above.

This example is paired with a blog post on LDA in Spark: http://databricks.com/blog
Spark: http://spark.apache.org/
*/

import scala.collection.mutable

welbornprod

#!/bin/bash

# Here are some embedded Python examples using Python3.
# They are put into functions for separation and clarity.


# Simple usage, only using python to print the date.
# This is not really a good example, because the `date`
# command works just as well.
function date_time {