Read & write data into cassandra using apache flink Java API - apache-spark

Question

I intend to use apache flink for read/write data into cassandra using flink. I was hoping to use flink-connector-cassandra, I don't find good documentation/examples for the connector.
Can you please point me to the right way for read and write data from cassandra using Apache Flink. I see only sink example which are purely for write ? Is apache flink meant for reading data too from cassandra similar to apache spark ?

Answer 1

I had the same question, and this is what I was looking for. I don't know if it is over simplified for what you need, but figured I should show it none the less.
ClusterBuilder cb = new ClusterBuilder() {
#Override
public Cluster buildCluster(Cluster.Builder builder) {
return builder.addContactPoint("urlToUse.com").withPort(9042).build();
}
};
CassandraInputFormat<Tuple2<String, String>> cassandraInputFormat = new CassandraInputFormat<>("SELECT * FROM example.cassandraconnectorexample", cb);
cassandraInputFormat.configure(null);
cassandraInputFormat.open(null);
Tuple2<String, String> testOutputTuple = new Tuple2<>();
cassandraInputFormat.nextRecord(testOutputTuple);
System.out.println("column1: " + testOutputTuple.f0);
System.out.println("column2: " + testOutputTuple.f1);
The way I figured this out was thanks to finding the code for the "CassandraInputFormat" class and seeing how it worked (http://www.javatips.net/api/flink-master/flink-connectors/flink-connector-cassandra/src/main/java/org/apache/flink/batch/connectors/cassandra/CassandraInputFormat.java). I honestly expected it to just be a format and not the full class of reading from Cassandra based on the name, and I have a feeling others might be thinking the same thing.

Answer 2

ClusterBuilder cb = new ClusterBuilder() {
#Override
public Cluster buildCluster(Cluster.Builder builder) {
return builder.addContactPoint("localhost").withPort(9042).build();
}
};
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
StreamTableEnvironment tableEnv = TableEnvironment.getTableEnvironment(env);
InputFormat inputFormat = new CassandraInputFormat<Tuple3<Integer, Integer, Integer>>("SELECT * FROM test.example;", cb);//, TypeInformation.of(Tuple3.class));
DataStreamSource t = env.createInput(inputFormat, TupleTypeInfo.of(new TypeHint<Tuple3<Integer, Integer,Integer>>() {}));
tableEnv.registerDataStream("t1",t);
Table t2 = tableEnv.sql("select * from t1");
t2.printSchema();

Answer 3

You can use RichFlatMapFunction to extend a class
class MongoMapper extends RichFlatMapFunction[JsonNode,JsonNode]{
var userCollection: MongoCollection[Document] = _
override def open(parameters: Configuration): Unit = {
// do something here like opening connection
val client: MongoClient = MongoClient("mongodb://localhost:10000")
userCollection = client.getDatabase("gp_stage").getCollection("users").withReadPreference(ReadPreference.secondaryPreferred())
super.open(parameters)
}
override def flatMap(event: JsonNode, out: Collector[JsonNode]): Unit = {
// Do something here per record and this function can make use of objects initialized via open
userCollection.find(Filters.eq("_id", somevalue)).limit(1).first().subscribe(
(result: Document) => {
// println(result)
},
(t: Throwable) =>{
println(t)
},
()=>{
out.collect(event)
}
)
}
}
}
Basically open function executes once per worker and flatmap executes it per record. The example is for mongo but can be similarly used for cassandra

Answer 4

In your case as I understand the first step of your pipeline is reading data from Cassandra rather than writing a RichFlatMapFunction you should write your own RichSourceFunction
As a reference you can have a look at simple implementation of WikipediaEditsSource.