internal static void DStreamTextFileSamples()
{
count = 0;
string directory = SparkCLRSamples.Configuration.SampleDataLocation;
string checkpointPath = Path.Combine(directory, "checkpoint");
SparkContext sc = SparkCLRSamples.SparkContext;
var b = sc.Broadcast <int>(0);
StreamingContext ssc = StreamingContext.GetOrCreate(checkpointPath,
() =>
{
StreamingContext context = new StreamingContext(sc, 2000);
context.Checkpoint(checkpointPath);
var lines = context.TextFileStream(Path.Combine(directory, "test"));
lines = context.Union(lines, lines);
var words = lines.FlatMap(l => l.Split(' '));
var pairs = words.Map(w => new KeyValuePair <string, int>(w, 1));
// since operations like ReduceByKey, Join and UpdateStateByKey are
// separate dstream transformations defined in CSharpDStream.scala
// an extra CSharpRDD is introduced in between these operations
var wordCounts = pairs.ReduceByKey((x, y) => x + y);
var join = wordCounts.Join(wordCounts, 2);
var state = join.UpdateStateByKey <string, Tuple <int, int>, int>(new UpdateStateHelper(b).Execute);
state.ForeachRDD((time, rdd) =>
{
// there's chance rdd.Take conflicts with ssc.Stop
if (stopFileServer)
{
return;
}
object[] taken = rdd.Take(10);
Console.WriteLine("-------------------------------------------");
Console.WriteLine("Time: {0}", time);
Console.WriteLine("-------------------------------------------");
foreach (object record in taken)
{
Console.WriteLine(record);
}
Console.WriteLine();
stopFileServer = count++ > 100;
});
return(context);
});
ssc.Start();
StartFileServer(directory, "words.txt", 100);
ssc.AwaitTermination();
ssc.Stop();
}
internal static void DStreamDirectKafkaWithRepartitionSample()
{
count = 0;
string directory = SparkCLRSamples.Configuration.SampleDataLocation;
string checkpointPath = Path.Combine(directory, "checkpoint");
StreamingContext ssc = StreamingContext.GetOrCreate(checkpointPath,
() =>
{
var conf = new SparkConf();
SparkContext sc = new SparkContext(conf);
StreamingContext context = new StreamingContext(sc, 2000L);
context.Checkpoint(checkpointPath);
var kafkaParams = new List <Tuple <string, string> > {
new Tuple <string, string>("metadata.broker.list", brokers),
new Tuple <string, string>("auto.offset.reset", "smallest")
};
conf.Set("spark.mobius.streaming.kafka.numPartitions." + topic, partitions.ToString());
var dstream = KafkaUtils.CreateDirectStream(context, new List <string> {
topic
}, kafkaParams, Enumerable.Empty <Tuple <string, long> >());
dstream.ForeachRDD((time, rdd) =>
{
long batchCount = rdd.Count();
int numPartitions = rdd.GetNumPartitions();
Console.WriteLine("-------------------------------------------");
Console.WriteLine("Time: {0}", time);
Console.WriteLine("-------------------------------------------");
Console.WriteLine("Count: " + batchCount);
Console.WriteLine("Partitions: " + numPartitions);
// only first batch has data and is repartitioned into 10 partitions
if (count++ == 0)
{
Assert.AreEqual(messages, batchCount);
Assert.IsTrue(numPartitions >= partitions);
}
else
{
Assert.AreEqual(0, batchCount);
Assert.IsTrue(numPartitions == 0);
}
});
return(context);
});
ssc.Start();
ssc.AwaitTermination();
}
static void Main(string[] args)
{
var sparkContext = new SparkContext(new SparkConf().SetAppName("SparkCLREventHub Example"));
var eventhubsParams = new Dictionary <string, string>()
{
{ "eventhubs.policyname", "<policyname>" },
{ "eventhubs.policykey", "<policykey>" },
{ "eventhubs.namespace", "<namespace>" },
{ "eventhubs.name", "<name>" },
{ "eventhubs.partition.count", "<partitioncount>" },
{ "eventhubs.consumergroup", "$default" },
{ "eventhubs.checkpoint.dir", "<hdfs path to eventhub checkpoint dir>" },
{ "eventhubs.checkpoint.interval", "<interval>" },
};
const int windowDurationInSecs = 5;
const int slideDurationInSecs = 5;
const string checkpointPath = "<hdfs path to spark checkpoint dir>";
//const string outputPath = "<hdfs path to output dir>";
const long slideDurationInMillis = 5000;
StreamingContext sparkStreamingContext = StreamingContext.GetOrCreate(checkpointPath,
() =>
{
var ssc = new StreamingContext(sparkContext, slideDurationInMillis);
ssc.Checkpoint(checkpointPath);
var stream = EventHubsUtils.CreateUnionStream(ssc, eventhubsParams.Select(v => new Tuple <string, string>(v.Key, v.Value)));
var countByLogLevelAndTime = stream
.Map(bytes => Encoding.UTF8.GetString(bytes))
.Filter(line => line.Contains(","))
.Map(line => line.Split(','))
.Map(columns => new Tuple <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.Item1, logLevelCountPair.Item2));
countByLogLevelAndTime.ForeachRDD(countByLogLevel =>
{
//dimensionalCount.SaveAsTextFile(string.Format("{0}/{1}", outputPath, Guid.NewGuid()));
var dimensionalCountCollection = countByLogLevel.Collect();
foreach (var dimensionalCountItem in dimensionalCountCollection)
{
Console.WriteLine(dimensionalCountItem);
}
});
return(ssc);
});
sparkStreamingContext.Start();
sparkStreamingContext.AwaitTermination();
}
static void Main(string[] args)
{
var sparkContext = new SparkContext(new SparkConf().SetAppName("SparkCLRKafka Example"));
const string topicName = "<topicName>";
var topicList = new List <string> {
topicName
};
var kafkaParams = new Dictionary <string, string> //refer to http://kafka.apache.org/documentation.html#configuration
{
{ "metadata.broker.list", "<kafka brokers list>" },
{ "auto.offset.reset", "smallest" }
};
var perTopicPartitionKafkaOffsets = new Dictionary <string, long>();
const int windowDurationInSecs = 5;
const int slideDurationInSecs = 5;
const string checkpointPath = "<hdfs path to spark checkpoint directory>";
const string appOutputPath = "<hdfs path to app output directory>";
const long slideDurationInMillis = 5000;
StreamingContext sparkStreamingContext = StreamingContext.GetOrCreate(checkpointPath,
() =>
{
var ssc = new StreamingContext(sparkContext, slideDurationInMillis);
ssc.Checkpoint(checkpointPath);
var stream = KafkaUtils.CreateDirectStream(ssc, topicList, kafkaParams.Select(v => new Tuple <string, string>(v.Key, v.Value)), perTopicPartitionKafkaOffsets.Select(v => new Tuple <string, long>(v.Key, v.Value)));
var countByLogLevelAndTime = stream
.Map(tuple => Encoding.UTF8.GetString(tuple.Item2))
.Filter(line => line.Contains(","))
.Map(line => line.Split(','))
.Map(columns => new Tuple <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.Item1, logLevelCountPair.Item2));
countByLogLevelAndTime.ForeachRDD(countByLogLevel =>
{
countByLogLevel.SaveAsTextFile(string.Format("{0}/{1}", appOutputPath, Guid.NewGuid()));
foreach (var logCount in countByLogLevel.Collect())
{
Console.WriteLine(logCount);
}
});
return(ssc);
});
sparkStreamingContext.Start();
sparkStreamingContext.AwaitTermination();
}
public static void Process(string AppName, string CheckpointPath, Dictionary <string, string> kafkaParams)
{
var sparkContext = new SparkContext(new SparkConf().SetAppName(AppName));
var topicList = new List <string> {
kafkaParams["topic"]
};
var perTopicPartitionKafkaOffsets = new Dictionary <string, long>();
const long slideDurationInMillis = 1000;
StreamingContext sparkStreamingContext = StreamingContext.GetOrCreate(CheckpointPath,
() =>
{
var ssc = new StreamingContext(sparkContext, slideDurationInMillis);
var stream = KafkaUtils.CreateDirectStream(ssc, topicList, kafkaParams, perTopicPartitionKafkaOffsets);
stream.Map(kvp =>
{
if (kvp.Value != null)
{
return(Encoding.UTF8.GetString(kvp.Value));
}
else
{
return(null);
}
}
).ForeachRDD(RDD =>
{
foreach (string line in RDD.Collect())
{
var message = JObject.Parse(line);
var _id = message.SelectToken("docid").ToString();
// =======================
// TODO: Process message
// =======================
}
}
);
ssc.Checkpoint(CheckpointPath);
return(ssc);
});
sparkStreamingContext.Start();
sparkStreamingContext.AwaitTermination();
}
static void Main(string[] args)
{
if (args.Length < 2)
{
Console.WriteLine("Usage: HdfsWordCount <checkpointDirectory> <inputDirectory>");
return;
}
string checkpointPath = args[0];
string inputDir = args[1];
StreamingContext ssc = StreamingContext.GetOrCreate(checkpointPath,
() =>
{
var sparkConf = new SparkConf();
sparkConf.SetAppName("HdfsWordCount");
var sc = new SparkContext(sparkConf);
StreamingContext context = new StreamingContext(sc, 30000);
context.Checkpoint(checkpointPath);
var lines = context.TextFileStream(inputDir);
var words = lines.FlatMap(l => l.Split(' '));
var pairs = words.Map(w => new KeyValuePair <string, int>(w, 1));
var wordCounts = pairs.ReduceByKey((x, y) => x + y);
wordCounts.ForeachRDD((time, rdd) =>
{
Console.WriteLine("-------------------------------------------");
Console.WriteLine("Time: {0}", time);
Console.WriteLine("-------------------------------------------");
object[] taken = rdd.Take(10);
foreach (object record in taken)
{
Console.WriteLine(record);
}
Console.WriteLine();
});
return(context);
});
ssc.Start();
ssc.AwaitTermination();
ssc.Stop();
}
public override void Run(Lazy <SparkContext> sparkContext, int currentTimes, int totalTimes)
{
DeleteCheckPointDirectory(currentTimes);
var options = Options as UnionTopicTestOptions;
var streamingContext = StreamingContext.GetOrCreate(options.CheckPointDirectory,
() =>
{
var ssc = new StreamingContext(sparkContext.Value, options.BatchSeconds * 1000L);
ssc.Checkpoint(options.CheckPointDirectory);
var stream1 = KafkaUtils.CreateDirectStream(ssc, new List <string> {
options.Topic1
}, kafkaParams, offsetsRange)
.Map(line => new RowIdCountTime().Deserialize(line.Value));
var stream2 = KafkaUtils.CreateDirectStream(ssc, new List <string> {
options.Topic2
}, kafkaParams, offsetsRange)
.Map(line => new RowIdCountTime().Deserialize(line.Value));
var stream = stream1.Union(stream2);
if (options.RePartition > 0)
{
stream = stream.Repartition(options.RePartition);
}
stream.ForeachRDD(rdd =>
{
rdd.Foreach(idCount =>
{
Console.WriteLine($"{NowMilli} {this.GetType().Name} : {idCount.ToString()}");
});
});
SaveStreamToFile(stream.Map(it => it.ToString()));
return(ssc);
});
streamingContext.Start();
WaitTerminationOrTimeout(streamingContext);
}
public override void Run(Lazy <SparkContext> sparkContext, int currentTimes, int totalTimes)
{
DeleteCheckPointDirectory(currentTimes);
var options = Options as WindowSlideTestOptions;
var allBeginTime = DateTime.Now;
var topicList = new List <string>(options.Topics.Split(";,".ToArray()));
ParseKafkaParameters();
for (var k = 0; options.TestTimes <= 0 || k < options.TestTimes; k++)
{
var beginTime = DateTime.Now;
//Logger.LogInfo("begin test[{0}]-{1} , sparkContext = {2}", k + 1, options.TestTimes > 0 ? options.TestTimes.ToString() : "infinite", sparkContext.Value);
var streamingContext = StreamingContext.GetOrCreate(options.CheckPointDirectory,
() =>
{
var ssc = new StreamingContext(sparkContext.Value, options.BatchSeconds * 1000L);
ssc.Checkpoint(options.CheckPointDirectory);
var stream = KafkaUtils.CreateDirectStream(ssc, topicList, kafkaParams, offsetsRange)
.Map(line => Encoding.UTF8.GetString(line.Value));
var pairs = stream.Map(new ParseKeyValueArray(options.ElementCount, options.ShowReceivedLines).Parse);
var reducedStream = pairs.ReduceByKeyAndWindow(
new ReduceHelper(options.CheckArrayAtFirst).Sum,
new ReduceHelper(options.CheckArrayAtFirst).InverseSum,
options.WindowSeconds,
options.SlideSeconds
);
reducedStream.ForeachRDD(new SumCountStatic().ForeachRDD <int[]>);
SaveStreamToFile(reducedStream);
return(ssc);
});
streamingContext.Start();
WaitTerminationOrTimeout(streamingContext);
}
}
static void Main(string[] args)
{
var checkpointPath = "";
var sparkContext = new SparkContext(new SparkConf());
var slideDurationInMillis = 10;
var topics = new List <string>();
var kafkaParams = new List <Tuple <string, string> >();
var perTopicPartitionKafkaOffsets = new List <Tuple <string, long> >();
var windowDurationInSecs = 10;
var slideDurationInSecs = 10;
StreamingContext sparkStreamingContext = StreamingContext.GetOrCreate(checkpointPath, () =>
{
var ssc = new StreamingContext(sparkContext, slideDurationInMillis);
ssc.Checkpoint(checkpointPath);
var stream = KafkaUtils.CreateDirectStream(ssc, topics, kafkaParams, perTopicPartitionKafkaOffsets);
var countByLogLevelAndTime = stream
.Map(kvp => Encoding.UTF8.GetString(kvp.Item2))
.Filter(line => line.Contains(","))
.Map(line => line.Split(','))
.Map(columns => new Tuple <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.Item1, logLevelCountPair.Item2));
countByLogLevelAndTime.ForeachRDD(countByLogLevel =>
{
foreach (var logCount in countByLogLevel.Collect())
{
Console.WriteLine(logCount);
}
});
return(ssc);
});
sparkStreamingContext.Start();
sparkStreamingContext.AwaitTermination();
Console.WriteLine("Hello World!");
}
internal static void DStreamTextFileSample()
{
count = 0;
string directory = SparkCLRSamples.Configuration.SampleDataLocation;
string checkpointPath = Path.Combine(directory, "checkpoint");
SparkContext sc = SparkCLRSamples.SparkContext;
var b = sc.Broadcast <int>(0);
StreamingContext ssc = StreamingContext.GetOrCreate(checkpointPath,
() =>
{
StreamingContext context = new StreamingContext(sc, 2000L); // batch interval is in milliseconds
context.Checkpoint(checkpointPath);
var lines = context.TextFileStream(Path.Combine(directory, "test"));
lines = context.Union(lines, lines);
var words = lines.FlatMap(l => l.Split(' '));
var pairs = words.Map(w => new Tuple <string, int>(w, 1));
// since operations like ReduceByKey, Join and UpdateStateByKey are
// separate dstream transformations defined in CSharpDStream.scala
// an extra CSharpRDD is introduced in between these operations
var wordCounts = pairs.ReduceByKey((x, y) => x + y);
var join = wordCounts.Window(2, 2).Join(wordCounts, 2);
var initialStateRdd = sc.Parallelize(new[] { new Tuple <string, int>("AAA", 88), new Tuple <string, int>("BBB", 88) });
var state = join.UpdateStateByKey(new UpdateStateHelper(b).Execute, initialStateRdd);
state.ForeachRDD((time, rdd) =>
{
// there's chance rdd.Take conflicts with ssc.Stop
if (stopFileServer)
{
return;
}
object[] taken = rdd.Take(10);
Console.WriteLine("-------------------------------------------");
Console.WriteLine("Time: {0}", time);
Console.WriteLine("-------------------------------------------");
foreach (object record in taken)
{
Console.WriteLine(record);
var countByWord = (Tuple <string, int>)record;
Assert.AreEqual(countByWord.Item2, countByWord.Item1 == "The" || countByWord.Item1 == "lazy" || countByWord.Item1 == "dog" ? 92 : 88);
}
Console.WriteLine();
stopFileServer = true;
});
return(context);
});
StartFileServer(ssc, directory, "words.txt");
ssc.Start();
ssc.AwaitTermination();
}
internal static void DStreamMapWithStateSample()
{
string directory = SparkCLRSamples.Configuration.SampleDataLocation;
string checkpointPath = Path.Combine(directory, "checkpoint");
StreamingContext ssc = StreamingContext.GetOrCreate(checkpointPath,
() =>
{
SparkContext sc = SparkCLRSamples.SparkContext;
StreamingContext context = new StreamingContext(sc, 10000L); // batch interval is in milliseconds
context.Checkpoint(checkpointPath);
var lines = context.TextFileStream(Path.Combine(directory, "test1"));
lines = context.Union(lines, lines);
var words = lines.FlatMap(l => l.Split(' '));
var pairs = words.Map(w => new KeyValuePair <string, int>(w, 1));
var wordCounts = pairs.ReduceByKey((x, y) => x + y);
var initialState = sc.Parallelize(new[] { new KeyValuePair <string, int>("NOT_A_WORD", 1024), new KeyValuePair <string, int>("dog", 10000), }, 1);
var stateSpec = new StateSpec <string, int, int, KeyValuePair <string, int> >((word, count, state) =>
{
if (state.IsTimingOut())
{
Console.WriteLine("Found timing out word: {0}", word);
return(new KeyValuePair <string, int>(word, state.Get()));
}
var sum = 0;
if (state.Exists())
{
sum = state.Get();
}
state.Update(sum + count);
Console.WriteLine("word: {0}, count: {1}", word, sum + count);
return(new KeyValuePair <string, int>(word, sum + count));
}).NumPartitions(1).InitialState(initialState).Timeout(TimeSpan.FromSeconds(30));
var snapshots = wordCounts.MapWithState(stateSpec).StateSnapshots();
snapshots.ForeachRDD((double time, RDD <dynamic> rdd) =>
{
Console.WriteLine("-------------------------------------------");
Console.WriteLine("Snapshots @ Time: {0}", time);
Console.WriteLine("-------------------------------------------");
foreach (KeyValuePair <string, int> record in rdd.Collect())
{
Console.WriteLine("[{0}, {1}]", record.Key, record.Value);
}
Console.WriteLine();
});
return(context);
});
ssc.Start();
StartFileServer(directory, "words.txt", 100);
ssc.AwaitTermination();
ssc.Stop();
}
