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Note that the following Kafka params cannot be set and the Kafka source or sink will throw an exception:

• key.deserializer: Keys are always deserialized as byte arrays with ByteArrayDeserializer. Use DataFrame operations to explicitly deserialize the keys.
• value.deserializer: Values are always deserialized as byte arrays with ByteArrayDeserializer. Use DataFrame operations to explicitly deserialize the values.

You'll have to register a UDF that invokes your deserializers instead

Similar to Read protobuf kafka message using spark structured streaming

The overall use of abstraction is decoupling. To work with an Employee, one does not need to know the implementation, only the interface and its contracts. This is, for example, used for Collections.sort(List list): the programmers of Collections.sort(...) did not need to know the implementation of a specific list in order to sort it. This provides the benefit that the implementation support future code that conforms to the List interface. This question is related in that respect (#selfPromotion). Less coupling leads to less friction and overall less fragile code.

That said, the example you provided is a poor one since it violates the Single Responsibility Principle: It is not the responsibility of an Employee instance to calculate the salary. For this, you should have a separate object that calculates the salary, based on an Employee-instance and some hours worked. Internally, this Uber-calculator could use a Chain of Responsibility, which hold one Calculator per Employee-Implementation, decoupling the Employee from how her/his salary is calculated. This provides the added benefit of extensability and flexibility: if the way a salary is calculated changes (e.g. maybe the company switches policy so that each FullTimeEmployee earns the same salary, or maybe the company wants to calculate the salary on a by-week instead of a by-month basis), other services using the FullTimeEmployee say unaffected).

You have to provide a CodedInputStream.

Change:

That style of formatting is not completely normal in most code but when you are using a builder it is quite common since part of using a builder is the ability to chain calls to look like what you posted for readability.

It replaces a long parameter list which also tend to have strange formatting.

The dots indicate a call to the return value of the method on the previous line (Note that the line before each line starting with "." has no semi-colon). Every builder method returns "this" so that it can be chained in this way.

If one wasn't interested in readability your example could be re-written like this:

The fact that it stuck on that line is normal. The program just expects the user's input from the console in order to proceed to the next line of code.

Really simple they changed the code. Instead of

ip.source(sIP); ip.destination(dIP);

Do

sIP = ip.source(); dIP = ip.destination();

The reason for the compilation error is that there's no Encoder in scope to convert a RDD with com.example.protobuf.SensorData to a Dataset of com.example.protobuf.SensorData.

Encoders (ExpressionEncoders to be exact) are used to convert InternalRow objects into JVM objects according to the schema (usually a case class or a Java bean).

There's a hope you can create an Encoder for the custom Java class using org.apache.spark.sql.Encoders object's bean method.

Creates an encoder for Java Bean of type T.

Something like the following:

Read the Javadoc - as you always should if you need to understand a class.

This class implements the Map interface with a hash table, using reference-equality in place of object-equality when comparing keys (and values). In other words, in an IdentityHashMap, two keys k1 and k2 are considered equal if and only if (k1==k2). (In normal Map implementations (like HashMap) two keys k1 and k2 are considered equal if and only if (k1==null ? k2==null : k1.equals(k2)).)

and

A typical use of this class is topology-preserving object graph transformations, such as serialization or deep-copying. To perform such a transformation, a program must maintain a "node table" that keeps track of all the object references that have already been processed. The node table must not equate distinct objects even if they happen to be equal.