SparkCLR (pronounced Sparkler) 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();

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

API Documentation

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

API Usage

SparkCLR API usage samples are available at:

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

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

Documents

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

Build Status

Ubuntu 14.04.3 LTS	Windows

Building, Running and Debugging SparkCLR

• Windows Instructions
• Linux Instructions

(Note: Tested with Spark 1.5.2)

License

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

Contribution

We welcome contributions. To contribute, follow the instructions in CONTRIBUTING.md.