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2021年行业大数据市场现状及发展趋势分析

随着社会的进步和信息通信技术的发展,大数据被广泛应用在各行业、各领域。大数据的广泛应用也意味着数据存储量越来越大,因而,近年来数据存储量呈爆发式增长。在大数据行业的快速增长过程中,中美两国以先进的技术优势占据行业重要地位。未来大数据行业在经历爆发式增长后,增速将逐渐放缓。 大数据行业正处在高速增长阶段,不论是数据存储规模还是整个行业的市场规模都在迅速成长,行业发展潜力巨大。 大数据储量爆发式增长 近两年来,大数据发展浪潮席卷。根据数据公司(IDC)的监测数据显示,2013年大数据储量为4.3ZB(相当于47.24亿个1TB容量的移动硬盘),2014年和2015年大数据储量分别为6.6ZB和8.6ZB。 近几年大数据储量的增速每年都保持在40%,2016年甚至达到了87.21%的增长率。2016年和2017年大数据储量分别为16.1ZB和21.6ZB,2018年大数据储量达到33.0ZB,2019年大数据储量达到41ZB。 2019年大数据整体市场规模达500亿美元 从市场规模来看,根据Wikibon发布的大数据市场报告数据显示。2014年以来,大数据硬件、软件和服务整体市场规模稳步提升。2019年大数据硬件、软件和服务整体市场规模达500亿美元。 中美两国在大数据储量方面占据重要地位 根据IDC新发布的统计数据,中国的数据产生量约占数据产生量的23%,美国的数据产生量占比约为21%,EMEA(欧洲、中东、非洲)的数据产生量占比约为30%,APJxC(日本和亚太)数据产生量占比约为18%,其他地区数据产生量占比约为8%。 大数据企业是资本追逐的热点 2019年,很多处于成长阶段的大数据初创企业拿到了不少的可观融资,其中包括:Databricks(4亿美元F轮),Celonis(2.9亿美元C轮),Peernova(7400万美元战略融资),Orbital Insight(5000万美元D轮)等。 2025年大数据市场规模将达920亿美元 虽然经济预期下行,但不论是企业还是政府对大数据的需求依然旺盛。据Wikibon预计,2020至2025年,大数据增长率将出现较小幅度的放缓,维持在10%-15%之间,据此推测,2025年大数据硬件、软件和服务整体市场规模将达到920亿美元。

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Azure平台 对Twitter 推文关键字进行实时大数据分析

Learn how to do real-timesentiment analysisof big data using HBase in an HDInsight (Hadoop) cluster. Social web sites are one of the major driving forces for Big Data adoption. Public APIs provided by sites like Twitter are a useful source of data for analyzing and understanding popular trends. In this tutorial, you will develop a console streaming service application and an ASP.NET Web application to perform the following: Get geo-tagged Tweets in real-time using the Twitter streaming API. Evaluate the sentiment of these Tweets. Store the sentiment information in HBase using the Microsoft HBase SDK. Plot the real-time statistical results on Bing maps using an ASP.NET Web application. A visualization of the tweets will look something like this: You will be able to query tweets with certain keywords to get a sense of the expressed opinion in tweets is positive, negative, or neutral. A complete Visual Studio solution sample can be found athttps://github.com/maxluk/tweet-sentiment. In this article Prerequisites Create a Twitter application Create a simple Twitter streaming service Create an Azure Website to visualize Twitter sentiment Next steps Prerequisites Before you begin this tutorial, you must have the following: An HBase cluster in HDInsight. For instructions on cluster provision, seeGet started using HBase with Hadoop in HDInsight. You will need the following data to go through the tutorial: CLUSTER PROPERTY DESCRIPTION HBase cluster name This is your HDInsight HBase cluster name. For example: https://myhbase.azurehdinsight.net/ Cluster user name The Hadoop user account name. The default Hadoop username isadmin. Cluster user password The Hadoop cluster user password. A workstationwith Visual Studio 2013 installed. For instructions, seeInstalling Visual Studio. Create a Twitter application ID and secrets The Twitter Streaming APIs useOAuthto authorize requests. The first step to use OAuth is to create a new application on the Twitter Developer site. To create Twitter application ID and secrets: Sign in tohttps://apps.twitter.com/.Click theSign up nowlink if you don't have a Twitter account. ClickCreate New App. EnterName,Description,Website. The Website field is not really used. It doesn't have to be a valid URL. The following table shows some sample values to use: FIELD VALUE Name MyHDInsightHBaseApp Description MyHDInsightHBaseApp Website http://www.myhdinsighthbaseapp.com CheckYes, I agree, and then clickCreate your Twitter application. Click thePermissionstab. The default permission isRead only. This is sufficient for this tutorial. Click theAPI Keystab. ClickCreate my access token. ClickTest OAuthin the upper right corner of the page. Write downAPI key,API secret,Access token, andAccess token secret. You will need the values later in the tutorial. Create a simple Twitter streaming service Create a console application to get Tweets, calculate Tweet sentiment score and send the processed Tweet words to HBase. To create the Visual Studio solution: OpenVisual Studio. From theFilemenu, point toNew, and then clickProject. Type or select the following values: Templates:Visual C# Template:Console Application Name:TweetSentimentStreaming Location:C:\Tutorials Solution name:TweetSentimentStreaming ClickOKto continue. To install Nuget packages and add SDK references: From theToolsmenu, clickNuget Package Manager, and then clickPackage Manager Console. The console panel will open at the bottom of the page. Use the following commands to install theTweetinvipackage, which is used to access the Twitter API, and theProtobuf-netpackage, which is used to serialize and deserialize objects. Install-Package TweetinviAPI Install-Package protobuf-net NOTE: The Microsoft Hbase SDK Nuget package is not available as of August 26th, 2014. The Github repo ishttps://github.com/hdinsight/hbase-sdk-for-net. Until the SDK is available, you must build the dll yourself. For instructions, seeGet started using HBase with Hadoop in HDInsight. FromSolution Explorer, right-clickReferences, and then clickAdd Reference. In the left pane, expandAssemblies, and then clickFramework. In the right pane, select the checkbox in front ofSystem.Configuration, and then clickOK. To define the Tweeter streaming service class: FromSolution explorer, right-clickTweetSentimentStreaming, point toAdd, and then clickClass. InName, typeHBaseWriter, and then clickAdd. InHBaseWriter.cs, add the following using statements on the top of the file: using System.IO; using System.Threading; using System.Globalization; using Microsoft.HBase.Client; using Tweetinvi.Core.Interfaces; using org.apache.hadoop.hbase.rest.protobuf.generated; InsideHbaseWriter.cs, add a new class callDictionaryItem: public class DictionaryItem { public string Type { get; set; } public int Length { get; set; } public string Word { get; set; } public string Pos { get; set; } public string Stemmed { get; set; } public string Polarity { get; set; } } This class structure is used to parse the sentiment dictionary file. The data is used to calculate sentiment score for each Tweet. Inside theHBaseWriterclass, define the following constants and variables: // HDinsight HBase cluster and HBase table information const string CLUSTERNAME = "https://<HBaseClusterName>.azurehdinsight.net/"; const string HADOOPUSERNAME = "<HadoopUserName>"; //the default name is "admin" const string HADOOPUSERPASSWORD = "<HaddopUserPassword>"; const string HBASETABLENAME = "tweets_by_words"; // Sentiment dictionary file and the punctuation characters const string DICTIONARYFILENAME = @"..\..\data\dictionary\dictionary.tsv"; private static char[] _punctuationChars = new[] { ' ', '!', '\"', '#', '$', '%', '&', '\'', '(', ')', '*', '+', ',', '-', '.', '/', //ascii 23--47 ':', ';', '<', '=', '>', '?', '@', '[', ']', '^', '_', '`', '{', '|', '}', '~' }; //ascii 58--64 + misc. // For writting to HBase HBaseClient client; // a sentiment dictionary for estimate sentiment. It is loaded from a physical file. Dictionary<string, DictionaryItem> dictionary; // use multithread write Thread writerThread; Queue<ITweet> queue = new Queue<ITweet>(); bool threadRunning = true; Set the constant values, including<HBaseClusterName>,<HadoopUserName>, and<HaddopUserPassword>. If you want to change the HBase table name, you must change the table name in the Web application accordingly. You will download and move the dictionary.tsv file to a specific folder later in the tutorial. Define the following functions inside theHBaseWriterclass: // This function connects to HBase, loads the sentiment dictionary, and starts the thread for writting. public HBaseWriter() { ClusterCredentials credentials = new ClusterCredentials(new Uri(CLUSTERNAME), HADOOPUSERNAME, HADOOPUSERPASSWORD); client = new HBaseClient(credentials); // create the HBase table if it doesn't exist if (!client.ListTables().name.Contains(HBASETABLENAME)) { TableSchema tableSchema = new TableSchema(); tableSchema.name = HBASETABLENAME; tableSchema.columns.Add(new ColumnSchema { name = "d" }); client.CreateTable(tableSchema); Console.WriteLine("Table \"{0}\" is created.", HBASETABLENAME); } // Load sentiment dictionary from a file LoadDictionary(); // Start a thread for writting to HBase writerThread = new Thread(new ThreadStart(WriterThreadFunction)); writerThread.Start(); } ~HBaseWriter() { threadRunning = false; } // Enqueue the Tweets received public void WriteTweet(ITweet tweet) { lock (queue) { queue.Enqueue(tweet); } } // Load sentiment dictionary from a file private void LoadDictionary() { List<string> lines = File.ReadAllLines(DICTIONARYFILENAME).ToList(); var items = lines.Select(line => { var fields = line.Split('\t'); var pos = 0; return new DictionaryItem { Type = fields[pos++], Length = Convert.ToInt32(fields[pos++]), Word = fields[pos++], Pos = fields[pos++], Stemmed = fields[pos++], Polarity = fields[pos++] }; }); dictionary = new Dictionary<string, DictionaryItem>(); foreach (var item in items) { if (!dictionary.Keys.Contains(item.Word)) { dictionary.Add(item.Word, item); } } } // Calculate sentiment score private int CalcSentimentScore(string[] words) { Int32 total = 0; foreach (string word in words) { if (dictionary.Keys.Contains(word)) { switch (dictionary[word].Polarity) { case "negative": total -= 1; break; case "positive": total += 1; break; } } } if (total > 0) { return 1; } else if (total < 0) { return -1; } else { return 0; } } // Popular a CellSet object to be written into HBase private void CreateTweetByWordsCells(CellSet set, ITweet tweet) { // Split the Tweet into words string[] words = tweet.Text.ToLower().Split(_punctuationChars); // Calculate sentiment score base on the words int sentimentScore = CalcSentimentScore(words); var word_pairs = words.Take(words.Length - 1) .Select((word, idx) => string.Format("{0} {1}", word, words[idx + 1])); var all_words = words.Concat(word_pairs).ToList(); // For each word in the Tweet add a row to the HBase table foreach (string word in all_words) { string time_index = (ulong.MaxValue - (ulong)tweet.CreatedAt.ToBinary()).ToString().PadLeft(20) + tweet.IdStr; string key = word + "_" + time_index; // Create a row var row = new CellSet.Row { key = Encoding.UTF8.GetBytes(key) }; // Add columns to the row, including Tweet identifier, language, coordinator(if available), and sentiment var value = new Cell { column = Encoding.UTF8.GetBytes("d:id_str"), data = Encoding.UTF8.GetBytes(tweet.IdStr) }; row.values.Add(value); value = new Cell { column = Encoding.UTF8.GetBytes("d:lang"), data = Encoding.UTF8.GetBytes(tweet.Language.ToString()) }; row.values.Add(value); if (tweet.Coordinates != null) { var str = tweet.Coordinates.Longitude.ToString() + "," + tweet.Coordinates.Latitude.ToString(); value = new Cell { column = Encoding.UTF8.GetBytes("d:coor"), data = Encoding.UTF8.GetBytes(str) }; row.values.Add(value); } value = new Cell { column = Encoding.UTF8.GetBytes("d:sentiment"), data = Encoding.UTF8.GetBytes(sentimentScore.ToString()) }; row.values.Add(value); set.rows.Add(row); } } // Write a Tweet (CellSet) to HBase public void WriterThreadFunction() { try { while (threadRunning) { if (queue.Count > 0) { CellSet set = new CellSet(); lock (queue) { do { ITweet tweet = queue.Dequeue(); CreateTweetByWordsCells(set, tweet); } while (queue.Count > 0); } // Write the Tweet by words cell set to the HBase table client.StoreCells(HBASETABLENAME, set); Console.WriteLine("\tRows written: {0}", set.rows.Count); } Thread.Sleep(100); } } catch (Exception ex) { Console.WriteLine("Exception: " + ex.Message); } } The code provides the following functionality: Connect to Hbase [ HBaseWriter() ]: Use the HBase SDK to create aClusterCredentialsobject with the cluster URL and the Hadoop user credential, and then create aHBaseClientobject using the ClusterCredentials object. Create HBase table [ HBaseWriter() ]: The method call isHBaseClient.CreateTable(). Write to HBase table [ WriterThreadFunction() ]: The method call isHBaseClient.StoreCells(). To complete the Program.cs: FromSolution Explorer, double-clickProgram.csto open it. At the beginning of the file, add the following using statements: using System.Configuration; using System.Diagnostics; using Tweetinvi; Inside theProgramclass, define the following constants: const string TWITTERAPPACCESSTOKEN = "<TwitterApplicationAccessToken"; const string TWITTERAPPACCESSTOKENSECRET = "TwitterApplicationAccessTokenSecret"; const string TWITTERAPPAPIKEY = "TwitterApplicationAPIKey"; const string TWITTERAPPAPISECRET = "TwitterApplicationAPISecret"; Set the constant values to match your Twitter application values. Modify theMain()function, so it looks like: static void Main(string[] args) { TwitterCredentials.SetCredentials(TWITTERAPPACCESSTOKEN, TWITTERAPPACCESSTOKENSECRET, TWITTERAPPAPIKEY, TWITTERAPPAPISECRET); Stream_FilteredStreamExample(); } Add the following function to the class: private static void Stream_FilteredStreamExample() { for (; ; ) { try { HBaseWriter hbase = new HBaseWriter(); var stream = Stream.CreateFilteredStream(); stream.AddLocation(Geo.GenerateLocation(-180, -90, 180, 90)); var tweetCount = 0; var timer = Stopwatch.StartNew(); stream.MatchingTweetReceived += (sender, args) => { tweetCount++; var tweet = args.Tweet; // Write Tweets to HBase hbase.WriteTweet(tweet); if (timer.ElapsedMilliseconds > 1000) { if (tweet.Coordinates != null) { Console.ForegroundColor = ConsoleColor.Green; Console.WriteLine("\n{0}: {1} {2}", tweet.Id, tweet.Language.ToString(), tweet.Text); Console.ForegroundColor = ConsoleColor.White; Console.WriteLine("\tLocation: {0}, {1}", tweet.Coordinates.Longitude, tweet.Coordinates.Latitude); } timer.Restart(); Console.WriteLine("\tTweets/sec: {0}", tweetCount); tweetCount = 0; } }; stream.StartStreamMatchingAllConditions(); } catch (Exception ex) { Console.WriteLine("Exception: {0}", ex.Message); } } } To download the sentiment dictionary file: Browse tohttps://github.com/maxluk/tweet-sentiment. ClickDownload ZIP. Extract the file locally. Copy the file from../tweet-sentiment/SimpleStreamingService/data/dictionary/dictionary.tsv. Paste the file to your solution underTweetSentimentStreaming/TweetSentimentStreaming/data/dictionary/dictionary.tsv. To run the streaming service: From Visual Studio, pressF5. The following is the console application screenshot: Keep the streaming console application running while you developing the Web application, So you have more data to use. Create an Azure Website to visualize Twitter sentiment In this section, you will create a ASP.NET MVC Web application to read the real-time sentiment data from HBase and plot the data on Bing maps. To create a ASP.NET MVC Web application: Open Visual Studio. ClickFile, clickNew, and then clickProject. Type or enter the following: Template category:Visual C#/Web Template:ASP.NET Web Application Name:TweetSentimentWeb Location:C:\Tutorials ClickOK. InSelect a template, clickMVC. InWindows Azure, clickManage Subscriptions. FromManage Windows Azure Subscriptions, clickSign in. Enter your Azure credential. Your Azure subscription information will be shown on the Accounts tab. ClickCloseto close the Manage Windows Azure Subscriptions window. FromNew ASP.NET Project - TweetSentimentWeb, ClickOK. FromConfigure Windows Azure Site Settings, select theRegionthat is closer to you. You don't need to specify a database server. ClickOK. To install Nuget packages: From theToolsmenu, clickNuget Package Manager, and then clickPackage Manager Console. The console panel is opened at the bottom of the page. Use the following command to install theProtobuf-netpackage, which is used to serialize and deserialize objects. Install-Package protobuf-net NOTE: The Microsoft Hbase SDK Nuget package is not available as of August 20th, 2014. The Github repo ishttps://github.com/hdinsight/hbase-sdk-for-net. Until the SDK is available, you must build the dll yourself. For instructions, seeGet started using HBase with Hadoop in HDInsight. To add HBaseReader class: FromSolution Explorer, expandTweetSentiment. Right-clickModels, clickAdd, and then clickClass. In Name, enterHBaseReader.cs, and then clickAdd. Replace the code with the following: using System; using System.Collections.Generic; using System.Linq; using System.Web; using System.Configuration; using System.Threading.Tasks; using System.Text; using Microsoft.HBase.Client; using org.apache.hadoop.hbase.rest.protobuf.generated; namespace TweetSentimentWeb.Models { public class HBaseReader { // For reading Tweet sentiment data from HDInsight HBase HBaseClient client; // HDinsight HBase cluster and HBase table information const string CLUSTERNAME = "<HBaseClusterName>"; const string HADOOPUSERNAME = "<HBaseClusterHadoopUserName>" const string HADOOPUSERPASSWORD = "<HBaseCluserUserPassword>"; const string HBASETABLENAME = "tweets_by_words"; // The constructor public HBaseReader() { ClusterCredentials creds = new ClusterCredentials( new Uri(CLUSTERNAME), HADOOPUSERNAME, HADOOPUSERPASSWORD); client = new HBaseClient(creds); } // Query Tweets sentiment data from the HBase table asynchronously public async Task<IEnumerable<Tweet>> QueryTweetsByKeywordAsync(string keyword) { List<Tweet> list = new List<Tweet>(); // Demonstrate Filtering the data from the past 6 hours the row key string timeIndex = (ulong.MaxValue - (ulong)DateTime.UtcNow.Subtract(new TimeSpan(6, 0, 0)).ToBinary()).ToString().PadLeft(20); string startRow = keyword + "_" + timeIndex; string endRow = keyword + "|"; Scanner scanSettings = new Scanner { batch = 100000, startRow = Encoding.UTF8.GetBytes(startRow), endRow = Encoding.UTF8.GetBytes(endRow) }; // Make async scan call ScannerInformation scannerInfo = await client.CreateScannerAsync(HBASETABLENAME, scanSettings); CellSet next; while ((next = await client.ScannerGetNextAsync(scannerInfo)) != null) { foreach (CellSet.Row row in next.rows) { // find the cell with string pattern "d:coor" var coordinates = row.values.Find(c => Encoding.UTF8.GetString(c.column) == "d:coor"); if (coordinates != null) { string[] lonlat = Encoding.UTF8.GetString(coordinates.data).Split(','); var sentimentField = row.values.Find(c => Encoding.UTF8.GetString(c.column) == "d:sentiment"); Int32 sentiment = 0; if (sentimentField != null) { sentiment = Convert.ToInt32(Encoding.UTF8.GetString(sentimentField.data)); } list.Add(new Tweet { Longtitude = Convert.ToDouble(lonlat[0]), Latitude = Convert.ToDouble(lonlat[1]), Sentiment = sentiment }); } if (coordinates != null) { string[] lonlat = Encoding.UTF8.GetString(coordinates.data).Split(','); } } } return list; } } public class Tweet { public string IdStr { get; set; } public string Text { get; set; } public string Lang { get; set; } public double Longtitude { get; set; } public double Latitude { get; set; } public int Sentiment { get; set; } } } Inside theHBaseReaderclass, change the constant values: CLUSTERNAME: The HBase cluster name. For example,https://.azurehdinsight.net/. HADOOPUSERNAME: The HBase cluster Hadoop user username. The default name isadmin. HADOOPUSERPASSWORD: The HBase cluster Hadoop user password. HBASETABLENAME= "tweets_by_words"; The HBase table name is "tweets_by_words". The values must match the values you sent in the streaming service, so that the Web application reads the data from the same HBase table. To add TweetsController controller: FromSolution Explorer, expandTweetSentimentWeb. Right-clickControllers, clickAdd, and then clickController. ClickWeb API 2 Controller - Empty, and then clickAdd. In Controller name, typeTweetsController, and then clickAdd. FromSolution Explorer, double-click TweetsController.cs to open the file. Modify the file, so it looks like the following:: using System; using System.Collections.Generic; using System.Linq; using System.Net; using System.Net.Http; using System.Web.Http; using System.Threading.Tasks; using TweetSentimentWeb.Models; namespace TweetSentimentWeb.Controllers { public class TweetsController : ApiController { HBaseReader hbase = new HBaseReader(); public async Task<IEnumerable<Tweet>> GetTweetsByQuery(string query) { return await hbase.QueryTweetsByKeywordAsync(query); } } } To add heatmap.js FromSolution Explorer, expandTweetSentimentWeb. Right-clickScripts, clickAdd, clickJavaScript File. In Item name, enterheatmap.js. Copy and paste the following code into the file. The code was written by Alastair Aitchison. For more information, seehttp://alastaira.wordpress.com/2011/04/15/bing-maps-ajax-v7-heatmap-library/. /******************************************************************************* * Author: Alastair Aitchison * Website: http://alastaira.wordpress.com * Date: 15th April 2011 * * Description: * This JavaScript file provides an algorithm that can be used to add a heatmap * overlay on a Bing Maps v7 control. The intensity and temperature palette * of the heatmap are designed to be easily customisable. * * Requirements: * The heatmap layer itself is created dynamically on the client-side using * the HTML5 <canvas> element, and therefore requires a browser that supports * this element. It has been tested on IE9, Firefox 3.6/4 and * Chrome 10 browsers. If you can confirm whether it works on other browsers or * not, I'd love to hear from you! * Usage: * The HeatMapLayer constructor requires: * - A reference to a map object * - An array or Microsoft.Maps.Location items * - Optional parameters to customise the appearance of the layer * (Radius,, Unit, Intensity, and ColourGradient), and a callback function * */ var HeatMapLayer = function (map, locations, options) { /* Private Properties */ var _map = map, _canvas, _temperaturemap, _locations = [], _viewchangestarthandler, _viewchangeendhandler; // Set default options var _options = { // Opacity at the centre of each heat point intensity: 0.5, // Affected radius of each heat point radius: 1000, // Whether the radius is an absolute pixel value or meters unit: 'meters', // Colour temperature gradient of the map colourgradient: { "0.00": 'rgba(255,0,255,20)', // Magenta "0.25": 'rgba(0,0,255,40)', // Blue "0.50": 'rgba(0,255,0,80)', // Green "0.75": 'rgba(255,255,0,120)', // Yellow "1.00": 'rgba(255,0,0,150)' // Red }, // Callback function to be fired after heatmap layer has been redrawn callback: null }; /* Private Methods */ function _init() { var _mapDiv = _map.getRootElement(); if (_mapDiv.childNodes.length >= 3 && _mapDiv.childNodes[2].childNodes.length >= 2) { // Create the canvas element _canvas = document.createElement('canvas'); _canvas.style.position = 'relative'; var container = document.createElement('div'); container.style.position = 'absolute'; container.style.left = '0px'; container.style.top = '0px'; container.appendChild(_canvas); _mapDiv.childNodes[2].childNodes[1].appendChild(container); // Override defaults with any options passed in the constructor _setOptions(options); // Load array of location data _setPoints(locations); // Create a colour gradient from the suppied colourstops _temperaturemap = _createColourGradient(_options.colourgradient); // Wire up the event handler to redraw heatmap canvas _viewchangestarthandler = Microsoft.Maps.Events.addHandler(_map, 'viewchangestart', _clearHeatMap); _viewchangeendhandler = Microsoft.Maps.Events.addHandler(_map, 'viewchangeend', _createHeatMap); _createHeatMap(); delete _init; } else { setTimeout(_init, 100); } } // Resets the heat map function _clearHeatMap() { var ctx = _canvas.getContext("2d"); ctx.clearRect(0, 0, _canvas.width, _canvas.height); } // Creates a colour gradient from supplied colour stops on initialisation function _createColourGradient(colourstops) { var ctx = document.createElement('canvas').getContext('2d'); var grd = ctx.createLinearGradient(0, 0, 256, 0); for (var c in colourstops) { grd.addColorStop(c, colourstops[c]); } ctx.fillStyle = grd; ctx.fillRect(0, 0, 256, 1); return ctx.getImageData(0, 0, 256, 1).data; } // Applies a colour gradient to the intensity map function _colouriseHeatMap() { var ctx = _canvas.getContext("2d"); var dat = ctx.getImageData(0, 0, _canvas.width, _canvas.height); var pix = dat.data; // pix is a CanvasPixelArray containing height x width x 4 bytes of data (RGBA) for (var p = 0, len = pix.length; p < len;) { var a = pix[p + 3] * 4; // get the alpha of this pixel if (a != 0) { // If there is any data to plot pix[p] = _temperaturemap[a]; // set the red value of the gradient that corresponds to this alpha pix[p + 1] = _temperaturemap[a + 1]; //set the green value based on alpha pix[p + 2] = _temperaturemap[a + 2]; //set the blue value based on alpha } p += 4; // Move on to the next pixel } ctx.putImageData(dat, 0, 0); } // Sets any options passed in function _setOptions(options) { for (attrname in options) { _options[attrname] = options[attrname]; } } // Sets the heatmap points from an array of Microsoft.Maps.Locations function _setPoints(locations) { _locations = locations; } // Main method to draw the heatmap function _createHeatMap() { // Ensure the canvas matches the current dimensions of the map // This also has the effect of resetting the canvas _canvas.height = _map.getHeight(); _canvas.width = _map.getWidth(); _canvas.style.top = -_canvas.height / 2 + 'px'; _canvas.style.left = -_canvas.width / 2 + 'px'; // Calculate the pixel radius of each heatpoint at the current map zoom if (_options.unit == "pixels") { radiusInPixel = _options.radius; } else { radiusInPixel = _options.radius / _map.getMetersPerPixel(); } var ctx = _canvas.getContext("2d"); // Convert lat/long to pixel location var pixlocs = _map.tryLocationToPixel(_locations, Microsoft.Maps.PixelReference.control); var shadow = 'rgba(0, 0, 0, ' + _options.intensity + ')'; var mapWidth = 256 * Math.pow(2, _map.getZoom()); // Create the Intensity Map by looping through each location for (var i = 0, len = pixlocs.length; i < len; i++) { var x = pixlocs[i].x; var y = pixlocs[i].y; if (x < 0) { x += mapWidth * Math.ceil(Math.abs(x / mapWidth)); } // Create radial gradient centred on this point var grd = ctx.createRadialGradient(x, y, 0, x, y, radiusInPixel); grd.addColorStop(0.0, shadow); grd.addColorStop(1.0, 'transparent'); // Draw the heatpoint onto the canvas ctx.fillStyle = grd; ctx.fillRect(x - radiusInPixel, y - radiusInPixel, 2 * radiusInPixel, 2 * radiusInPixel); } // Apply the specified colour gradient to the intensity map _colouriseHeatMap(); // Call the callback function, if specified if (_options.callback) { _options.callback(); } } /* Public Methods */ this.Show = function () { if (_canvas) { _canvas.style.display = ''; } }; this.Hide = function () { if (_canvas) { _canvas.style.display = 'none'; } }; // Sets options for intensity, radius, colourgradient etc. this.SetOptions = function (options) { _setOptions(options); } // Sets an array of Microsoft.Maps.Locations from which the heatmap is created this.SetPoints = function (locations) { // Reset the existing heatmap layer _clearHeatMap(); // Pass in the new set of locations _setPoints(locations); // Recreate the layer _createHeatMap(); } // Removes the heatmap layer from the DOM this.Remove = function () { _canvas.parentNode.parentNode.removeChild(_canvas.parentNode); if (_viewchangestarthandler) { Microsoft.Maps.Events.removeHandler(_viewchangestarthandler); } if (_viewchangeendhandler) { Microsoft.Maps.Events.removeHandler(_viewchangeendhandler); } _locations = null; _temperaturemap = null; _canvas = null; _options = null; _viewchangestarthandler = null; _viewchangeendhandler = null; } // Call the initialisation routine _init(); }; // Call the Module Loaded method Microsoft.Maps.moduleLoaded('HeatMapModule'); To add tweetStream.js: FromSolution Explorer, expandTweetSentimentWeb. Right-clickScripts, clickAdd, clickJavaScript File. In Item name, entertwitterStream.js. Copy and paste the following code into the file: var liveTweetsPos = []; var liveTweets = []; var liveTweetsNeg = []; var map; var heatmap; var heatmapNeg; var heatmapPos; function initialize() { // Initialize the map var options = { credentials: "AvFJTZPZv8l3gF8VC3Y7BPBd0r7LKo8dqKG02EAlqg9WAi0M7la6zSIT-HwkMQbx", center: new Microsoft.Maps.Location(23.0, 8.0), mapTypeId: Microsoft.Maps.MapTypeId.ordnanceSurvey, labelOverlay: Microsoft.Maps.LabelOverlay.hidden, zoom: 2.5 }; var map = new Microsoft.Maps.Map(document.getElementById('map_canvas'), options); // Heatmap options for positive, neutral and negative layers var heatmapOptions = { // Opacity at the centre of each heat point intensity: 0.5, // Affected radius of each heat point radius: 15, // Whether the radius is an absolute pixel value or meters unit: 'pixels' }; var heatmapPosOptions = { // Opacity at the centre of each heat point intensity: 0.5, // Affected radius of each heat point radius: 15, // Whether the radius is an absolute pixel value or meters unit: 'pixels', colourgradient: { 0.0: 'rgba(0, 255, 255, 0)', 0.1: 'rgba(0, 255, 255, 1)', 0.2: 'rgba(0, 255, 191, 1)', 0.3: 'rgba(0, 255, 127, 1)', 0.4: 'rgba(0, 255, 63, 1)', 0.5: 'rgba(0, 127, 0, 1)', 0.7: 'rgba(0, 159, 0, 1)', 0.8: 'rgba(0, 191, 0, 1)', 0.9: 'rgba(0, 223, 0, 1)', 1.0: 'rgba(0, 255, 0, 1)' } }; var heatmapNegOptions = { // Opacity at the centre of each heat point intensity: 0.5, // Affected radius of each heat point radius: 15, // Whether the radius is an absolute pixel value or meters unit: 'pixels', colourgradient: { 0.0: 'rgba(0, 255, 255, 0)', 0.1: 'rgba(0, 255, 255, 1)', 0.2: 'rgba(0, 191, 255, 1)', 0.3: 'rgba(0, 127, 255, 1)', 0.4: 'rgba(0, 63, 255, 1)', 0.5: 'rgba(0, 0, 127, 1)', 0.7: 'rgba(0, 0, 159, 1)', 0.8: 'rgba(0, 0, 191, 1)', 0.9: 'rgba(0, 0, 223, 1)', 1.0: 'rgba(0, 0, 255, 1)' } }; // Register and load the Client Side HeatMap Module Microsoft.Maps.registerModule("HeatMapModule", "scripts/heatmap.js"); Microsoft.Maps.loadModule("HeatMapModule", { callback: function () { // Create heatmap layers for positive, neutral and negative tweets heatmapPos = new HeatMapLayer(map, liveTweetsPos, heatmapPosOptions); heatmap = new HeatMapLayer(map, liveTweets, heatmapOptions); heatmapNeg = new HeatMapLayer(map, liveTweetsNeg, heatmapNegOptions); } }); $("#searchbox").val("xbox"); $("#searchBtn").click(onsearch); $("#positiveBtn").click(onPositiveBtn); $("#negativeBtn").click(onNegativeBtn); $("#neutralBtn").click(onNeutralBtn); $("#neutralBtn").button("toggle"); } function onsearch() { var uri = 'api/tweets?query='; var query = $('#searchbox').val(); $.getJSON(uri + query) .done(function (data) { liveTweetsPos = []; liveTweets = []; liveTweetsNeg = []; // On success, 'data' contains a list of tweets. $.each(data, function (key, item) { addTweet(item); }); if (!$("#neutralBtn").hasClass('active')) { $("#neutralBtn").button("toggle"); } onNeutralBtn(); }) .fail(function (jqXHR, textStatus, err) { $('#statustext').text('Error: ' + err); }); } function addTweet(item) { //Add tweet to the heat map arrays. var tweetLocation = new Microsoft.Maps.Location(item.Latitude, item.Longtitude); if (item.Sentiment > 0) { liveTweetsPos.push(tweetLocation); } else if (item.Sentiment < 0) { liveTweetsNeg.push(tweetLocation); } else { liveTweets.push(tweetLocation); } } function onPositiveBtn() { if ($("#neutralBtn").hasClass('active')) { $("#neutralBtn").button("toggle"); } if ($("#negativeBtn").hasClass('active')) { $("#negativeBtn").button("toggle"); } heatmapPos.SetPoints(liveTweetsPos); heatmapPos.Show(); heatmapNeg.Hide(); heatmap.Hide(); $('#statustext').text('Tweets: ' + liveTweetsPos.length + " " + getPosNegRatio()); } function onNeutralBtn() { if ($("#positiveBtn").hasClass('active')) { $("#positiveBtn").button("toggle"); } if ($("#negativeBtn").hasClass('active')) { $("#negativeBtn").button("toggle"); } heatmap.SetPoints(liveTweets); heatmap.Show(); heatmapNeg.Hide(); heatmapPos.Hide(); $('#statustext').text('Tweets: ' + liveTweets.length + " " + getPosNegRatio()); } function onNegativeBtn() { if ($("#positiveBtn").hasClass('active')) { $("#positiveBtn").button("toggle"); } if ($("#neutralBtn").hasClass('active')) { $("#neutralBtn").button("toggle"); } heatmapNeg.SetPoints(liveTweetsNeg); heatmapNeg.Show(); heatmap.Hide();; heatmapPos.Hide();; $('#statustext').text('Tweets: ' + liveTweetsNeg.length + "\t" + getPosNegRatio()); } function getPosNegRatio() { if (liveTweetsNeg.length == 0) { return ""; } else { var ratio = liveTweetsPos.length / liveTweetsNeg.length; var str = parseFloat(Math.round(ratio * 10) / 10).toFixed(1); return "Positive/Negative Ratio: " + str; } } To modify the layout.cshtml: FromSolution Explorer, expandTweetSentimentWeb, expandViews, expandShared, and then double-click _Layout.cshtml. Replace the content with the following: <!DOCTYPE html> <html> <head> <meta charset="utf-8" /> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>@ViewBag.Title</title> @Styles.Render("~/Content/css") @Scripts.Render("~/bundles/modernizr") <!-- Bing Maps --> <script type="text/javascript" src="http://ecn.dev.virtualearth.net/mapcontrol/mapcontrol.ashx?v=7.0&mkt=en-gb"></script> <!-- Spatial Dashboard JavaScript --> <script src="~/Scripts/twitterStream.js" type="text/javascript"></script> </head> <body onload="initialize()"> <div class="navbar navbar-inverse navbar-fixed-top"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-collapse"> <span class="icon-bar"></span> <span class="icon-bar"></span> <span class="icon-bar"></span> </button> </div> <div class="navbar-collapse collapse"> <div class="row"> <ul class="nav navbar-nav col-lg-5"> <li class="col-lg-12"> <div class="navbar-form"> <input id="searchbox" type="search" class="form-control"> <button type="button" id="searchBtn" class="btn btn-primary">Go</button> </div> </li> </ul> <ul class="nav navbar-nav col-lg-7"> <li> <div class="navbar-form"> <div class="btn-group" data-toggle="buttons-radio"> <button type="button" id="positiveBtn" class="btn btn-primary">Positive</button> <button type="button" id="neutralBtn" class="btn btn-primary">Neutral</button> <button type="button" id="negativeBtn" class="btn btn-primary">Negative</button> </div> </div> </li> <li><span id="statustext" class="navbar-text"></span></li> </ul> </div> </div> </div> </div> <div class="map_container"> @RenderBody() </div> @Scripts.Render("~/bundles/jquery") @Scripts.Render("~/bundles/bootstrap") @RenderSection("scripts", required: false) </body> </html> To modify the Index.cshtml FromSolution Explorer, expandTweetSentimentWeb, expandViews, expandHome, and then double-clickIndex.cshtml. Replace the content with the following: @{ ViewBag.Title = "Tweet Sentiment"; } <div class="map_container"> <div id="map_canvas"/> </div> To modify the site.css file: FromSolution Explorer, expandTweetSentimentWeb, expandContent, and then double-clickSite.css. Append the following code to the file. /* make container, and thus map, 100% width */ .map_container { width: 100%; height: 100%; } #map_canvas{ height:100%; } #tweets{ position: absolute; top: 60px; left: 75px; z-index:1000; font-size: 30px; } To modify the global.asax file: FromSolution Explorer, expandTweetSentimentWeb, and then double-clickGlobal.asax. Add the following using statement: using System.Web.Http; Add the following lines inside theApplication_Start()function: // Register API routes GlobalConfiguration.Configure(WebApiConfig.Register); Modify the registration of the API routes to make Web API controller work inside of the MVC application. To run the Web application: Verify the streaming service console application is still running. So you can see the real-time changes. PressF5to run the web application: In the text box, enter a keyword, and then clickGo. Depending on the data collected in the HBase table, some keywords might not be found. Try some common keywords, such as "love", "xbox", "playstation" and so on. Toggle amongPositive,Neutral, andNegativeto compare sentiment on the subject. Let the streaming service running for another hour, and then search the same keyword, and compare the results. Optionally, you can deploy the application to an Azure Web site. For instructions, seeGet started with Azure Web Sites and ASP.NET. Next Steps In this tutorial we have learned how to get Tweets, analyze the sentiment of Tweets, save the sentiment data to HBase, and present the real-time Twitter sentiment data to Bing maps. To learn more, see: Get started with HDInsight Analyze Twitter data with Hadoop in HDInsight Analyze flight delay data using HDInsight Develop C# Hadoop streaming programs for HDInsight Develop Java MapReduce programs for HDInsight

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