I am consuming data from a Kafka topic using the following consumer setup:
val consumer = {
val properties = new Properties()
properties.put(ConsumerConfig.GROUP_ID_CONFIG, "some_consumer_group")
properties.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, streamingConfig.getString("kafka.brokers"))
properties.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, classOf[StringDeserializer])
properties.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, classOf[KafkaJsonDeserializer[Sample]])
properties.put("json.value.type",classOf[Sample])
properties.put(ConsumerConfig.MAX_POLL_RECORDS_CONFIG, streamingConfig.getInt("kafka.maxPollRecords"): java.lang.Integer)
properties.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, streamingConfig.getInt("kafka.sessionTimeoutMs"): java.lang.Integer)
properties.put(ConsumerConfig.HEARTBEAT_INTERVAL_MS_CONFIG, streamingConfig.getInt("kafka.heartbeatIntervalMs"): java.lang.Integer)
val consumer = new KafkaConsumer[String, Sample](properties)
consumer.subscribe(util.Arrays.asList(topic))
consumer
}
while the payload is represented by the following case class
case class Sample(properties: Map[String, String],eventType: String)
The problem is that during the deserialization the following errors are produced
Caused by: org.apache.kafka.common.errors.SerializationException: com.fasterxml.jackson.databind.exc.InvalidDefinitionException: Cannot construct instance of `org.service.Sample` (no Creators, like default construct, exist): cannot deserialize from Object value (no delegate- or property-based Creator)
at [Source: (byte[])"{}"; line: 1, column: 2]
Caused by: com.fasterxml.jackson.databind.exc.InvalidDefinitionException: Cannot construct instance of `org.service.Sample` (no Creators, like default construct, exist): cannot deserialize from Object value (no delegate- or property-based Creator)
at [Source: (byte[])"{}"; line: 1, column: 2]
If I was using Java the solution for this is straighforward: Just add a default constructor. What happens in the case of Scala case classes though? I know that the Jackson object mappers can be configured with a jackson-module-scala which takes care of case classes but due to the way the KafkaJsonSerializer is configured I cannot mess with its object mappers - this is its configure method:
protected void configure(KafkaJsonSerializerConfig config) {
boolean prettyPrint = config.getBoolean("json.indent.output");
this.objectMapper = new ObjectMapper();
this.objectMapper.configure(SerializationFeature.INDENT_OUTPUT, prettyPrint);
}
So how can I go about this error here?
I'm trying to use Redis to store some cache data for my entity, which has different types of fields inside, for example,
public class Job {
private String id;
private Date createTime; //Long
private String submitterName;
private JobDefinition jobDef; //Another class
}
There are more fields and due to the fact that several fields are updated more frequently than others, I decided to save this job as a Hashmap in Redis with each field as a key. Here the nested object like jobDef is not important so I used Jackson2JsonRedisSerializer as hashValueSerializer for RedisTemplate and the jobDef obj will just be serialized as a long JSON string, which is totally fine in my case.
But I don't know how can I effectively deserialize the whole job object back from Redis. The type I set to deserializer is like Jackson2JsonRedisSerializer(Map.class) but it complains when deserializing String keys and values.
So is this an invalid usage with RedisTemplate or how should I configure my serializer for it?
EDIT:
Adding more code details,
#Autowired
private StringRedisTemplate redisTemplate; //Here I'm using a String template as I need to use the same redisTemplate for some key-value/list operations too
Map jobHash= new ObjectMapper().convertValue(job, Map.class);
redisTemplate.setHashValueSerializer(new Jackson2JsonRedisSerializer(Map.class));
redisTemplate.opsForHash().putAll("job:"+job.getId(), jobHash); //After this the job hash shows up in Redis as I expected, while the jobDef member is serialized and saved as a JSON string
Map jobMap = redisTemplate.opsForHash().entries("job:" + job.getId()); //But this won't work as it'll throw exception complaining cannot deserialize a String value to Map. But when I set Jackson2JsonRedisSerializer(String.class) it throws exception that cannot resolve the byte code
2nd EDIT:
If using JdkSerializationRedisSerializer as HashValueSerializer in RedisTemplate then the deserialization works fine, however the downside for using this one is the value stored in Redis is not the same human readable string value as when using Jackson2JsonRedisSerializer.
The Jackson2JsonRedisSerializer does not include mapping information into the actual hash structure.
The resulting Redis HASH results in something like:
127.0.0.1:6379> hgetall job:1
1) "id"
2) "\"1\""
3) "createTime"
4) "1455778716799"
5) "submitterName"
6) "\"Jon Snow\""
7) "jobDef"
8) "{\"def\":\"nightwatch\"}"
The ObjectMapper produces a LinkedHashMap for the JobDefinition entry which fails to deserialize as the type is unknown.
Using the GenericJackson2JsonRedisSerializer includes type information so the resulting Redis HASH looks like this:
127.0.0.1:6379> hgetall job:1
1) "id"
2) "\"1\""
...
7) "jobDef"
8) "{\"#class\":\"java.util.LinkedHashMap\",\"def\":\"nightwatch\"}"
This allows to deserialize values correctly.
Another approach would be to NOT use a specific HashValueSerializer but instead use a DecoratingStringHashMapper along with the StringRedisTemplate.
DecoratingStringHashMapper mapper = new DecoratingStringHashMapper<Job>(
new JacksonHashMapper<Job>(Job.class));
template.opsForHash().putAll("job:" + job.id, mapper.toHash(job));
Map jobMap = template.opsForHash().entries("job:" + job.id);
The DecoratingStringHashMapper will produce a Redis Hash as follows:
127.0.0.1:6379> hgetall job:1
1) "id"
2) "1"
3) "createTime"
4) "1455780810643"
5) "submitterName"
6) "Jon Snow"
7) "jobDef"
8) "{def=nightwatch}"
Unfortunately there is no Jackson2HashMapper. Please vote for DATAREDIS-423 and help us prioritize.
With this jackson-module-scala wrapper
object Json {
private val ma = new ObjectMapper with ScalaObjectMapper
ma.registerModule(DefaultScalaModule)
ma.setSerializationInclusion(Include.NON_NULL)
def jRead[T: Manifest](value: String): T = ma.readValue[T](value)
def jWrite(value: Any) = ma.writer.writeValueAsString(value)
def jNode(value: String) = ma.readTree(value)
}
I try to read subtype (it is just simplified use case without real work):
object TestJTrait extends App {
trait T1
object TestJ { def apply[X <: T1: Manifest](s: String): X = jRead[X](s) }
case class C1(i: Int) extends T1
TestJ(jWrite(C1(42)))
}
But this attempt results in the error:
Exception in thread "main" com.fasterxml.jackson.databind.JsonMappingException: Can not instantiate abstract type [simple type, class scala.runtime.Nothing$] (need to add/enable type information?)
at [Source: {"i":42}; line: 1, column: 2]
at com.fasterxml.jackson.databind.JsonMappingException.from(JsonMappingException.java:148)
at com.fasterxml.jackson.databind.deser.std.ThrowableDeserializer.deserializeFromObject(ThrowableDeserializer.java:73)
at com.fasterxml.jackson.databind.deser.BeanDeserializer.deserialize(BeanDeserializer.java:124)
at com.fasterxml.jackson.databind.ObjectMapper._readMapAndClose(ObjectMapper.java:3051)
at com.fasterxml.jackson.databind.ObjectMapper.readValue(ObjectMapper.java:2160)
at com.fasterxml.jackson.module.scala.experimental.ScalaObjectMapper$class.readValue(ScalaObjectMapper.scala:180)
Can anybody, please, suggest a workaround to get the intended behaveur?
Since T1 is a trait (abstract type) when deserializing it will try to create an instance of T1 it has no information about C1. You need to hint it.
TestJ[C1](jWrite(C1(42)) should help
If you also have case class C2(i: Int) extends T1, how could it choose between reading C1 or C2? And if you don't, how could it know that you don't? After all, C2 could be anywhere in your program, perhaps in a class which hasn't been loaded yet (and so could C1!). Manifest in [X <: T1: Manifest] won't help either, since the type argument can't be inferred.
It looks like when I try to serialize a case class extending from Seq it gets handeled as a Seq and all additional fields are omitted.
Serializing just leads to a Standard Sequence without the additional fields. Whereas deserialization fails.
Anybody knows what I'am doing wrong here?
Code:
// Definition of class
case class IntSeq(count: Int, ints: Seq[Int]) extends Seq[Int] {
def length: Int = ints.length
def iterator: Iterator[Int] = ints.iterator
def apply(idx: Int) = ints(idx)
}
// type Hints
implicit val hints = Serialization.formats( ShortTypeHints(List(classOf[IntSeq])) )
lazy val testIntSeq = IntSeq(5, List(1,2,3,4,5))
val ser = Serialization.write[IntSeq](testIntSeq)
// ser: String = [1,2,3,4,5]
Serialization.read[IntSeq](ser) // Hurray: org.json4s.package$MappingException: unknown error
Without discussing why such a class is useful... How would you manually encode such object?
In JSON you can have dictionaries and lists, so you cannot expect a list to have extra named attributes.
You can make your IntSeq class to have a list attribute and not extend Seq itself (and maybe provide an automatic conversion), so your JSON could look like:
{'length' : 5, 'ints' : [1, 2, 3, 4, 5]}
I read Scala Functions (part of Another tour of Scala). In that post he stated:
Methods and functions are not the same thing
But he didn't explain anything about it. What was he trying to say?
Jim has got this pretty much covered in his blog post, but I'm posting a briefing here for reference.
First, let's see what the Scala Specification tell us. Chapter 3 (types) tell us about Function Types (3.2.9) and Method Types (3.3.1). Chapter 4 (basic declarations) speaks of Value Declaration and Definitions (4.1), Variable Declaration and Definitions (4.2) and Functions Declarations and Definitions (4.6). Chapter 6 (expressions) speaks of Anonymous Functions (6.23) and Method Values (6.7). Curiously, function values is spoken of one time on 3.2.9, and no where else.
A Function Type is (roughly) a type of the form (T1, ..., Tn) => U, which is a shorthand for the trait FunctionN in the standard library. Anonymous Functions and Method Values have function types, and function types can be used as part of value, variable and function declarations and definitions. In fact, it can be part of a method type.
A Method Type is a non-value type. That means there is no value - no object, no instance - with a method type. As mentioned above, a Method Value actually has a Function Type. A method type is a def declaration - everything about a def except its body.
Value Declarations and Definitions and Variable Declarations and Definitions are val and var declarations, including both type and value - which can be, respectively, Function Type and Anonymous Functions or Method Values. Note that, on the JVM, these (method values) are implemented with what Java calls "methods".
A Function Declaration is a def declaration, including type and body. The type part is the Method Type, and the body is an expression or a block. This is also implemented on the JVM with what Java calls "methods".
Finally, an Anonymous Function is an instance of a Function Type (ie, an instance of the trait FunctionN), and a Method Value is the same thing! The distinction is that a Method Value is created from methods, either by postfixing an underscore (m _ is a method value corresponding to the "function declaration" (def) m), or by a process called eta-expansion, which is like an automatic cast from method to function.
That is what the specs say, so let me put this up-front: we do not use that terminology! It leads to too much confusion between so-called "function declaration", which is a part of the program (chapter 4 -- basic declarations) and "anonymous function", which is an expression, and "function type", which is, well a type -- a trait.
The terminology below, and used by experienced Scala programmers, makes one change from the terminology of the specification: instead of saying function declaration, we say method. Or even method declaration. Furthermore, we note that value declarations and variable declarations are also methods for practical purposes.
So, given the above change in terminology, here's a practical explanation of the distinction.
A function is an object that includes one of the FunctionX traits, such as Function0, Function1, Function2, etc. It might be including PartialFunction as well, which actually extends Function1.
Let's see the type signature for one of these traits:
trait Function2[-T1, -T2, +R] extends AnyRef
This trait has one abstract method (it has a few concrete methods as well):
def apply(v1: T1, v2: T2): R
And that tell us all that there is to know about it. A function has an apply method which receives N parameters of types T1, T2, ..., TN, and returns something of type R. It is contra-variant on the parameters it receives, and co-variant on the result.
That variance means that a Function1[Seq[T], String] is a subtype of Function1[List[T], AnyRef]. Being a subtype means it can be used in place of it. One can easily see that if I'm going to call f(List(1, 2, 3)) and expect an AnyRef back, either of the two types above would work.
Now, what is the similarity of a method and a function? Well, if f is a function and m is a method local to the scope, then both can be called like this:
val o1 = f(List(1, 2, 3))
val o2 = m(List(1, 2, 3))
These calls are actually different, because the first one is just a syntactic sugar. Scala expands it to:
val o1 = f.apply(List(1, 2, 3))
Which, of course, is a method call on object f. Functions also have other syntactic sugars to its advantage: function literals (two of them, actually) and (T1, T2) => R type signatures. For example:
val f = (l: List[Int]) => l mkString ""
val g: (AnyVal) => String = {
case i: Int => "Int"
case d: Double => "Double"
case o => "Other"
}
Another similarity between a method and a function is that the former can be easily converted into the latter:
val f = m _
Scala will expand that, assuming m type is (List[Int])AnyRef into (Scala 2.7):
val f = new AnyRef with Function1[List[Int], AnyRef] {
def apply(x$1: List[Int]) = this.m(x$1)
}
On Scala 2.8, it actually uses an AbstractFunction1 class to reduce class sizes.
Notice that one can't convert the other way around -- from a function to a method.
Methods, however, have one big advantage (well, two -- they can be slightly faster): they can receive type parameters. For instance, while f above can necessarily specify the type of List it receives (List[Int] in the example), m can parameterize it:
def m[T](l: List[T]): String = l mkString ""
I think this pretty much covers everything, but I'll be happy to complement this with answers to any questions that may remain.
One big practical difference between a method and a function is what return means. return only ever returns from a method. For example:
scala> val f = () => { return "test" }
<console>:4: error: return outside method definition
val f = () => { return "test" }
^
Returning from a function defined in a method does a non-local return:
scala> def f: String = {
| val g = () => { return "test" }
| g()
| "not this"
| }
f: String
scala> f
res4: String = test
Whereas returning from a local method only returns from that method.
scala> def f2: String = {
| def g(): String = { return "test" }
| g()
| "is this"
| }
f2: String
scala> f2
res5: String = is this
function A function can be invoked with a list of arguments to produce a
result. A function has a parameter list, a body, and a result type.
Functions that are members of a class, trait, or singleton object are
called methods. Functions defined inside other functions are called
local functions. Functions with the result type of Unit are called procedures.
Anonymous functions in source code are called function literals.
At run time, function literals are instantiated into objects called
function values.
Programming in Scala Second Edition.
Martin Odersky - Lex Spoon - Bill Venners
Let Say you have a List
scala> val x =List.range(10,20)
x: List[Int] = List(10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
Define a Method
scala> def m1(i:Int)=i+2
m1: (i: Int)Int
Define a Function
scala> (i:Int)=>i+2
res0: Int => Int = <function1>
scala> x.map((x)=>x+2)
res2: List[Int] = List(12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
Method Accepting Argument
scala> m1(2)
res3: Int = 4
Defining Function with val
scala> val p =(i:Int)=>i+2
p: Int => Int = <function1>
Argument to function is Optional
scala> p(2)
res4: Int = 4
scala> p
res5: Int => Int = <function1>
Argument to Method is Mandatory
scala> m1
<console>:9: error: missing arguments for method m1;
follow this method with `_' if you want to treat it as a partially applied function
Check the following Tutorial that explains passing other differences with examples like other example of diff with Method Vs Function, Using function as Variables, creating function that returned function
Functions don't support parameter defaults. Methods do. Converting from a method to a function loses parameter defaults. (Scala 2.8.1)
There is a nice article here from which most of my descriptions are taken.
Just a short comparison of Functions and Methods regarding my understanding. Hope it helps:
Functions:
They are basically an object. More precisely, functions are objects with an apply method; Therefore, they are a little bit slower than methods because of their overhead. It is similar to static methods in the sense that they are independent of an object to be invoked.
A simple example of a function is just like bellow:
val f1 = (x: Int) => x + x
f1(2) // 4
The line above is nothing except assigning one object to another like object1 = object2. Actually the object2 in our example is an anonymous function and the left side gets the type of an object because of that. Therefore, now f1 is an object(Function). The anonymous function is actually an instance of Function1[Int, Int] that means a function with 1 parameter of type Int and return value of type Int.
Calling f1 without the arguments will give us the signature of the anonymous function (Int => Int = )
Methods:
They are not objects but assigned to an instance of a class,i.e., an object. Exactly the same as method in java or member functions in c++ (as Raffi Khatchadourian pointed out in a comment to this question) and etc.
A simple example of a method is just like bellow:
def m1(x: Int) = x + x
m1(2) // 4
The line above is not a simple value assignment but a definition of a method. When you invoke this method with the value 2 like the second line, the x is substituted with 2 and the result will be calculated and you get 4 as an output. Here you will get an error if just simply write m1 because it is method and need the input value. By using _ you can assign a method to a function like bellow:
val f2 = m1 _ // Int => Int = <function1>
Here is a great post by Rob Norris which explains the difference, here is a TL;DR
Methods in Scala are not values, but functions are. You can construct a function that delegates to a method via η-expansion (triggered by the trailing underscore thingy).
with the following definition:
a method is something defined with def and a value is something you can assign to a val
In a nutshell (extract from the blog):
When we define a method we see that we cannot assign it to a val.
scala> def add1(n: Int): Int = n + 1
add1: (n: Int)Int
scala> val f = add1
<console>:8: error: missing arguments for method add1;
follow this method with `_' if you want to treat it as a partially applied function
val f = add1
Note also the type of add1, which doesn’t look normal; you can’t declare a variable of type (n: Int)Int. Methods are not values.
However, by adding the η-expansion postfix operator (η is pronounced “eta”), we can turn the method into a function value. Note the type of f.
scala> val f = add1 _
f: Int => Int = <function1>
scala> f(3)
res0: Int = 4
The effect of _ is to perform the equivalent of the following: we construct a Function1 instance that delegates to our method.
scala> val g = new Function1[Int, Int] { def apply(n: Int): Int = add1(n) }
g: Int => Int = <function1>
scala> g(3)
res18: Int = 4
Practically, a Scala programmer only needs to know the following three rules to use functions and methods properly:
Methods defined by def and function literals defined by => are functions. It is defined in page 143, Chapter 8 in the book of Programming in Scala, 4th edition.
Function values are objects that can be passed around as any values. Function literals and partially applied functions are function values.
You can leave off the underscore of a partially applied function if a function value is required at a point in the code. For example: someNumber.foreach(println)
After four editions of Programming in Scala, it is still an issue for people to differentiate the two important concepts: function and function value because all editions don't give a clear explanation. The language specification is too complicated. I found the above rules are simple and accurate.
In Scala 2.13, unlike functions, methods can take/return
type parameters (polymorphic methods)
implicit parameters
dependent types
However, these restrictions are lifted in dotty (Scala 3) by Polymorphic function types #4672, for example, dotty version 0.23.0-RC1 enables the following syntax
Type parameters
def fmet[T](x: List[T]) = x.map(e => (e, e))
val ffun = [T] => (x: List[T]) => x.map(e => (e, e))
Implicit parameters (context parameters)
def gmet[T](implicit num: Numeric[T]): T = num.zero
val gfun: [T] => Numeric[T] ?=> T = [T] => (using num: Numeric[T]) => num.zero
Dependent types
class A { class B }
def hmet(a: A): a.B = new a.B
val hfun: (a: A) => a.B = hmet
For more examples, see tests/run/polymorphic-functions.scala
The difference is subtle but substantial and it is related to the type system in use (besides the nomenclature coming from Object Oriented or Functional paradigm).
When we talk about a function, we talk about the type Function: it being a type, an instance of it can be passed around as input or output to other functions (at least in the case of Scala).
When we talk about a method (of a class), we are actually talking about the type represented by the class it is part of: that is, the method is just a component of a larger type, and cannot be passed around by itself. It must be passed around with the instance of the type it is part of (i.e. the instance of the class).
A method belongs to an object (usually the class, trait or object in which you define it), whereas a function is by itself a value, and because in Scala every value is an object, therefore, a function is an object.
For example, given a method and a function below:
def timesTwoMethod(x :Int): Int = x * 2
def timesTwoFunction = (x: Int) => x * 2
The second def is an object of type Int => Int (the syntactic sugar for Function1[Int, Int]).
Scala made functions objects so they could be used as first-class entities. This way you can pass functions to other functions as arguments.
However, Scala can also treat methods as functions via a mechanism called Eta Expansion.
For example, the higher-order function map defined on List, receives another function f: A => B as its only parameter. The next two lines are equivalent:
List(1, 2, 3).map(timesTwoMethod)
List(1, 2, 3).map(timesTwoFunction)
When the compiler sees a def given in a place where a function is needed, it automatically converts the method into an equivalent function.
A method operates on an object but a function doesn't.
Scala and C++ has Fuction but in JAVA, you have to imitate them with static methods.