# Mobius: C# API for Spark

Mobius adds C# language binding to Apache Spark, enabling the implementation of Spark driver code and data processing operations in C#.

For example, the word count sample in Apache Spark can be implemented in C# as follows :

var lines = sparkContext.TextFile(@"hdfs://path/to/input.txt");  
var words = lines.FlatMap(s => s.Split(' '));
var wordCounts = words.Map(w => new KeyValuePair<string, int>(w.Trim(), 1))  
                      .ReduceByKey((x, y) => x + y);  
var wordCountCollection = wordCounts.Collect();  
wordCounts.SaveAsTextFile(@"hdfs://path/to/wordcount.txt");  

A simple DataFrame application using TempTable may look like the following:

var reqDataFrame = sqlContext.TextFile(@"hdfs://path/to/requests.csv");
var metricDataFrame = sqlContext.TextFile(@"hdfs://path/to/metrics.csv");
reqDataFrame.RegisterTempTable("requests");
metricDataFrame.RegisterTempTable("metrics");
// C0 - guid in requests DataFrame, C3 - guid in metrics DataFrame  
var joinDataFrame = GetSqlContext().Sql(  
    "SELECT joinedtable.datacenter" +
         ", MAX(joinedtable.latency) maxlatency" +
         ", AVG(joinedtable.latency) avglatency " + 
    "FROM (" +
       "SELECT a.C1 as datacenter, b.C6 as latency " +  
       "FROM requests a JOIN metrics b ON a.C0  = b.C3) joinedtable " +   
    "GROUP BY datacenter");
joinDataFrame.ShowSchema();
joinDataFrame.Show();

A simple DataFrame application using DataFrame DSL may look like the following:

// C0 - guid, C1 - datacenter
var reqDataFrame = sqlContext.TextFile(@"hdfs://path/to/requests.csv")  
                             .Select("C0", "C1");    
// C3 - guid, C6 - latency   
var metricDataFrame = sqlContext.TextFile(@"hdfs://path/to/metrics.csv", ",", false, true)
                                .Select("C3", "C6"); //override delimiter, hasHeader & inferSchema
var joinDataFrame = reqDataFrame.Join(metricDataFrame, reqDataFrame["C0"] == metricDataFrame["C3"])
                                .GroupBy("C1");
var maxLatencyByDcDataFrame = joinDataFrame.Agg(new Dictionary<string, string> { { "C6", "max" } });
maxLatencyByDcDataFrame.ShowSchema();
maxLatencyByDcDataFrame.Show();

A simple Spark Streaming application that processes messages from Kafka using C# may be implemented using the following code:

StreamingContext sparkStreamingContext = StreamingContext.GetOrCreate(checkpointPath, () =>
    {
      var ssc = new StreamingContext(sparkContext, slideDurationInMillis);
      ssc.Checkpoint(checkpointPath);
      var stream = KafkaUtils.CreateDirectStream(ssc, topicList, kafkaParams, perTopicPartitionKafkaOffsets);
      //message format: [timestamp],[loglevel],[logmessage]
      var countByLogLevelAndTime = stream
                                    .Map(kvp => Encoding.UTF8.GetString(kvp.Value))
                                    .Filter(line => line.Contains(","))
                                    .Map(line => line.Split(','))
                                    .Map(columns => new KeyValuePair<string, int>(
                                                          string.Format("{0},{1}", columns[0], columns[1]), 1))
                                    .ReduceByKeyAndWindow((x, y) => x + y, (x, y) => x - y,
                                                          windowDurationInSecs, slideDurationInSecs, 3)
                                    .Map(logLevelCountPair => string.Format("{0},{1}",
                                                          logLevelCountPair.Key, logLevelCountPair.Value));
      countByLogLevelAndTime.ForeachRDD(countByLogLevel =>
      {
          foreach (var logCount in countByLogLevel.Collect())
              Console.WriteLine(logCount);
      });
      return ssc;
    });
sparkStreamingContext.Start();
sparkStreamingContext.AwaitTermination();

Refer to Mobius\csharp\Samples directory and sample usage for complete samples.

API Documentation

Refer to Mobius C# API documentation for the list of Spark's data processing operations supported in Mobius.

API Usage

Mobius API usage samples are available at:

• Examples folder which contains standalone C# projects that can be used as templates to start developing Mobius applications

• Samples project which uses a comprehensive set of Mobius APIs to implement samples that are also used for functional validation of APIs

• Mobius performance test scenarios implemented in C# and Scala for side by side comparison of Spark driver code

Documents

Refer to the docs folder for design overview and other info on Mobius

Build Status

Ubuntu 14.04.3 LTS	Windows	Unit test coverage

Getting Started

	Windows	Linux
Build & run unit tests	Build in Windows	Build in Linux
Run samples (functional tests) in local mode	Samples in Windows	Samples in Linux
Run examples in local mode	Examples in Windows	Examples in Linux
Run Mobius app	Standalone cluster YARN cluster	Linux cluster Azure HDInsight Spark Cluster AWS EMR Spark Cluster

Useful Links

• Configuration parameters in Mobius
• Troubleshoot errors in Mobius
• Debug Mobius apps

Supported Spark Versions

Mobius is built and tested with Apache Spark 1.4.1, 1.5.2 and 1.6.*.

Releases

Mobius releases are available at https://github.com/Microsoft/Mobius/releases. References needed to build C# Spark driver applicaiton using Mobius are also available in NuGet

Refer to mobius-release-info.md for the details on versioning policy and the contents of the release.

License

Mobius is licensed under the MIT license. See LICENSE file for full license information.

Community

[](https://twitter.com/intent/tweet?text=@MobiusForSpark [your tweet] via @GitHub)

• Mobius project welcomes contributions. To contribute, follow the instructions in CONTRIBUTING.md

• Options to ask your question to the Mobius community

  • create issue on GitHub
  • create post with "sparkclr" tag in Stack Overflow
  • join chat at Mobius room in Gitter
  • tweet @MobiusForSpark

Code of Conduct

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.