Why I can do this in Java:
import javax.swing.GroupLayout.Group;
but if I do the same in Scala (by using Ammonite), I get this:
value Group is not a member of object javax.swing.GroupLayout possible
cause: maybe a semicolon is missing before `value Group'? import
javax.swing.GroupLayout.Group
Is it due to the fact that Group is a public class derived from a private class called Spring?.
I can import neither SequentialGroup nor ParallelGroup.
Is it a bug in Scala?
I'm using Java 11 and Scala 2.12.10.
Scala 2.13.1 also fails. :-(
I need the import, for defining a generic method that can have a Group parameter, that could be either a ParallelGroup or a SequentialGroup.
I'd like to generate a generic method that takes as a parameter a Group, that could be either a ParallelGroup or a SequientialGroup
That would be a type projection
def method(group: GroupLayout#Group) = ...
or if you also have the layout the group belongs to,
def method(layout: GroupLayout)(group: layout.Group) = ...
or
val layout: GroupLayout = ...
def method(group: layout.Group) = ...
Related
I'm trying to get the SQLContext instance from one module in another module. The first module instantiates it to an implicit sqlContext and I had (erroneously) thought that I could then use an implicit parameter in the second module, but the compiler informs me that:
could not find implicit value for parameter sqlCtxt: org.apache.spark.sql.SQLContext
Here's the skeletal setup I have (I have elided imports and details):
-----
// Application.scala
-----
package apps
object Application extends App {
val env = new SparkEnvironment("My app", ...)
try {
// Call methods from various packages that use code from internally DFExtensions.scala
}
}
-----
// SparkEnvironment.scala
-----
package common
class SparkEnvironment(val app: String, ...) {
#transient lazy val conf: SparkConf = new SparkConf().setAppName(app)
#transient implicit lazy val sc: SparkContext = new SparkContext(conf)
#transient implicit lazy val sqlContext: SQLContext = new SQLContext(sc)
...
}
-----
// DFExtensions.scala
-----
package util
object DFExtensions {
private def myFun(...)(implicit sqlCtxt: SQLContext) = { ... }
implicit final class DFExt(val df: DataFrame) extends AnyVal {
// Extension methods for DataFrame where myFun is supposed to be used -- causes exception!
}
}
Since it's a multi-project sbt setup I don't want to pass around the instance env to all related objects because the stuff in util is really a shared library. Each sub-project (i.e. app) has its own instance created in the main method.
Because myFun is only called from the implicit class DFExt I thought about creating an implicit just before each call à la implicit val sqlCtxt = df.sqlContext and that compiles but it's kind of ugly and I would not need the implicit in SparkEnvironment any longer.
According to this discussion the implicit sqlContext instance is not in scope, hence compilation fails. I'm not sure a package object would work because the implicit value and parameter are in different packages.
Is what I'm trying to achieve even possible? Is there a better alternative?
The idea is to have several sub-projects that use the same libraries and core functions to share the same project. They are typically updated together, so it's nice to have them in a single place. Most of the library functions directly work on data frames and other structures in Spark, but occasionally I need to do something that requires an instance of SparkContext or SQLContext, for instance write a query with sqlContext.sql as some syntax is not yet natively supported (e.g. flattening with outer lateral views).
Each sub-project has its own main method that creates an implicit instance. Obviously the libraries do not 'know' about this as they are in different packages and I don't pass around the instances. I had thought that somehow implicits are looked for at runtime, so that when an application runs there is an instance of SQLContext defined as an implicit. It's possible that a) it's not in scope because it's in a different package or b) what I'm trying to do is just a bad idea.
Currently there is only one main method because I first have to split the application in multiple components, which I have not done yet.
Just in case it helps:
Spark 1.4.1
Scala 2.10
sbt 0.13.8
Because myFun is only called from the implicit class DFExt I thought about creating an implicit just before each call à la implicit val sqlCtxt = df.sqlContext and that compiles but it's kind of ugly and I would not need the implicit in SparkEnvironment any longer.
Just put the implicit and myFun inside DFExt:
implicit final class DFExt(val df: DataFrame) extends AnyVal {
private implicit def sqlCtxt: SqlContext = df.sqlContext
// no need to take an implicit parameter, as sqlCtxt is already in scope
private def myFun(...) = ...
// The extension methods can now use sqlCtxt and/or myFun freely
}
You could also make sqlCtxt a val, but then: 1) DFExt can't extend AnyVal anymore; 2) it needs to be initialized even if the extension method you call doesn't need it; 3) any calls to sqlCtxt are likely to be inlined, so you are just accessing a val from df instead of this anyway. If they aren't, this means you are using it far too little to matter.
The following code executes fine in a scala shell given snakeyaml version 1.17
import org.yaml.snakeyaml.Yaml
import org.yaml.snakeyaml.constructor.Constructor
import scala.collection.mutable.ListBuffer
import scala.beans.BeanProperty
class EmailAccount {
#scala.beans.BeanProperty var accountName: String = null
override def toString: String = {
return s"acct ($accountName)"
}
}
val text = """accountName: Ymail Account"""
val yaml = new Yaml(new Constructor(classOf[EmailAccount]))
val e = yaml.load(text).asInstanceOf[EmailAccount]
println(e)
However when running in spark (2.0.0 in this case) the resulting error is:
org.yaml.snakeyaml.constructor.ConstructorException: Can't construct a java object for tag:yaml.org,2002:EmailAccount; exception=java.lang.NoSuchMethodException: EmailAccount.<init>()
in 'string', line 1, column 1:
accountName: Ymail Account
^
at org.yaml.snakeyaml.constructor.Constructor$ConstructYamlObject.construct(Constructor.java:350)
at org.yaml.snakeyaml.constructor.BaseConstructor.constructObject(BaseConstructor.java:182)
at org.yaml.snakeyaml.constructor.BaseConstructor.constructDocument(BaseConstructor.java:141)
at org.yaml.snakeyaml.constructor.BaseConstructor.getSingleData(BaseConstructor.java:127)
at org.yaml.snakeyaml.Yaml.loadFromReader(Yaml.java:450)
at org.yaml.snakeyaml.Yaml.load(Yaml.java:369)
... 48 elided
Caused by: org.yaml.snakeyaml.error.YAMLException: java.lang.NoSuchMethodException: EmailAccount.<init>()
at org.yaml.snakeyaml.constructor.Constructor$ConstructMapping.createEmptyJavaBean(Constructor.java:220)
at org.yaml.snakeyaml.constructor.Constructor$ConstructMapping.construct(Constructor.java:190)
at org.yaml.snakeyaml.constructor.Constructor$ConstructYamlObject.construct(Constructor.java:346)
... 53 more
Caused by: java.lang.NoSuchMethodException: EmailAccount.<init>()
at java.lang.Class.getConstructor0(Class.java:2810)
at java.lang.Class.getDeclaredConstructor(Class.java:2053)
at org.yaml.snakeyaml.constructor.Constructor$ConstructMapping.createEmptyJavaBean(Constructor.java:216)
... 55 more
I launched the scala shell with
scala -classpath "/home/placey/snakeyaml-1.17.jar"
I launched the spark shell with
/home/placey/Downloads/spark-2.0.0-bin-hadoop2.7/bin/spark-shell --master local --jars /home/placey/snakeyaml-1.17.jar
Solution
Create a self-contained application and run it using spark-submit instead of using spark-shell.
I've created a minimal project for you as a gist here. All you need to do is put both files (build.sbt and Main.scala) in some directory, then run:
sbt package
in order to create a JAR. The JAR will be in target/scala-2.11/sparksnakeyamltest_2.11-1.0.jar or a similar location. You can get SBT from here if you haven't used it yet. Finally, you can run the project:
/home/placey/Downloads/spark-2.0.0-bin-hadoop2.7/bin/spark-submit --class "Main" --master local --jars /home/placey/snakeyaml-1.17.jar target/scala-2.11/sparksnakeyamltest_2.11-1.0.jar
The output should be:
[many lines of Spark's log)]
acct (Ymail Account)
[more lines of Spark's log)]
Explanation
Spark's shell (REPL) transforms all classes you define in it by adding $iw parameter to your constructors. I've explained it here. SnakeYAML expects a zero-parameter constructor for JavaBean-like classes, but there isn't one, so it fails.
You can try this yourself:
scala> class Foo() {}
defined class Foo
scala> classOf[Foo].getConstructors()
res0: Array[java.lang.reflect.Constructor[_]] = Array(public Foo($iw))
scala> classOf[Foo].getConstructors()(0).getParameterCount
res1: Int = 1
As you can see, Spark transforms the constructor by adding a parameter of type $iw.
Alternative solutions
Define your own Constructor
If you really need to get it working in the shell, you could define your own class implementing org.yaml.snakeyaml.constructor.BaseConstructor and make sure that $iw gets passed to constructors, but this is a lot of work (I actually wrote my own Constructor in Scala for security reasons some time ago, so I have some experience with this).
You could also define a custom Constructor hard-coded to instantiate a specific class (EmailAccount in your case) similar to the DiceConstructor shown in SnakeYAML's documentation. This is much easier, but requires writing code for each class you want to support.
Example:
case class EmailAccount(accountName: String)
class EmailAccountConstructor extends org.yaml.snakeyaml.constructor.Constructor {
val emailAccountTag = new org.yaml.snakeyaml.nodes.Tag("!emailAccount")
this.rootTag = emailAccountTag
this.yamlConstructors.put(emailAccountTag, new ConstructEmailAccount)
private class ConstructEmailAccount extends org.yaml.snakeyaml.constructor.AbstractConstruct {
def construct(node: org.yaml.snakeyaml.nodes.Node): Object = {
// TODO: This is fine for quick prototyping in a REPL, but in a real
// application you should probably add type checks.
val mnode = node.asInstanceOf[org.yaml.snakeyaml.nodes.MappingNode]
val mapping = constructMapping(mnode)
val name = mapping.get("accountName").asInstanceOf[String]
new EmailAccount(name)
}
}
}
You can save this as a file and load it in the REPL using :load filename.scala.
Bonus advantage of this solution is that it can create immutable case class instances directly. Unfortunately Scala REPL seems to have issues with imports, so I've used fully qualified names.
Don't use JavaBeans
You can also just parse YAML documents as simple Java maps:
scala> val yaml2 = new Yaml()
yaml2: org.yaml.snakeyaml.Yaml = Yaml:1141996301
scala> val e2 = yaml2.load(text)
e2: Object = {accountName=Ymail Account}
scala> val map = e2.asInstanceOf[java.util.Map[String, Any]]
map: java.util.Map[String,Any] = {accountName=Ymail Account}
scala> map.get("accountName")
res4: Any = Ymail Account
This way SnakeYAML won't need to use reflection.
However, since you're using Scala, I recommend trying
MoultingYAML, which is a Scala wrapper for SnakeYAML. It parses YAML documents to simple Java types and then maps them to Scala types (even your own types like EmailAccount).
In Java, while type arguments are erased in runtime, it is possible to find the actual type arguments passed to a superclass:
class Derived extends Base<String> {
// ...
}
ParameterizedType type = (ParameterizedType)Derived.class.getGenericSuperclass();
Type[] args = type.getActualTypeArguments(); // gives {String.class}
While I can use the same Java reflection to Scala class, It does not catch Scala's value types:
class Base[T]
class Derived extends Base[Int]
classOf[Derived]
.getGenericSuperclass
.asInstanceOf[ParameterizedType]
.getActualTypeArguments // gives {Object.class}, not {int.class}
Is it possible to determine the value type used when extending from a generic superclass? I am loading classes from a jar file so it'd be best to achieve this only using a java.lang.Class instance.
In Java reflection you won't be able to obtain Int and other AnyVal types because they are handled specially by the compiler and if they are used generically, they will be represented by Object. However, you can use Scala reflection, and it is wholly possible to go from Java reflection to Scala reflection. Here's how:
import scala.reflect.runtime.universe._
class Base[T]
class Derived extends Base[Int]
object Main extends App {
val rm = runtimeMirror(getClass.getClassLoader) // whatever class loader you're using
val derivedSym = rm.staticClass(classOf[Derived].getName)
val baseSym = rm.staticClass(classOf[Base[_]].getName)
val TypeRef(_, _, params) = derivedSym.typeSignature.baseType(baseSym)
println(s"$derivedSym extends $baseSym[${params.mkString(", ")}]")
}
Unfortunately, unless you know exactly what you are searching for, you will have hard time finding proper documentation. I have found the answer on scala-users mailing list. Scala reflection is still experimental and, AFAIK, it will probably be superseded by a better one in future Scala versions.
How does one invoke the following java method from scala?
public static Config parseMap(Map<String, ? extends Object> values,
String originDescription) {
I have attempted to invoke it as follows:
val SAMPLE_PROPS_MAP : Map[String,AnyRef] = Map("hiveSaveFreq" -> new java.lang.Long(10L), "aggSeconds" -> new java.lang.Long(3))
val props = ConfigFactory.parseMap(SAMPLE_PROPS_MAP,"props"))
However Intellij complains:
Cannot resolve symbol parseMap
To ensure this were not other issues (e.g. incorrect version of libraries):
val props = ConfigFactory.parseMap(null,"props"))
works fine. Also, the intellisense bubble does confirm the signature as being shown above (having Map).
However Intellij complains:
So then what is the Scala equivalent to the ? extends Object
The issue is not on the ? extends Object type boundary declaration but rather on the Map definition. The signature you have is:
public static Config parseMap(**java.util.Map**<String, ? extends Object> values, String originDescription)
and you are passing it a scala.collection.immutable.Map
You need to convert your scala map to a java map, either by creating a java map "by hand" or using the facilities in the scala API:
import scala.collection.JavaConverters._
val SamplePropsMap : Map[String,AnyRef] = Map("hiveSaveFreq" -> new java.lang.Long(10L), "aggSeconds" -> new java.lang.Long(3))
val props = ConfigFactory.parseMap(SamplePropsMap.asJava,"props"))
(note: The implicit methods in JavaConverters are the recommended way to deal with java-scala conversions, by using javaCollection.asScala and scalaCollection.asJava. Also note that in Scala, the convention for 'constants' is camel-case starting with a capital. e.g. CamelCase)
The Map needs to be converted to java format, as follows:
import collection.JavaConversions._
val props = ConfigFactory.parseMap(mapAsJavaMap(SAMPLE_PROPS_MAP))
I tried to run one example from Programming in Scala but compiler gives me error:
Description Resource Path Location Type
illegal start of statement (no modifiers allowed here) ChecksumAcc.sc /HelloWorld/src line 3 Scala Problem
basically complains about private
import scala.collection.mutable.Map
object ChecksumAcc {
private val cache = Map[String, Int]()
}
I'm using Eclipse for Scala worksheet. Same after updating. I believe it uses 2.9.3 scala compiler. Why doesn't it compile?
Not sure what your actual question is, but the Scala worksheet has some special rules (as indicated by the very clear error message...). One thing you can do if you have to use the worksheet, is to put all your code inside a Worksheet object like this:
object Worksheet {
import scala.collection.mutable.Map
object ChecksumAcc {
private val cache = Map[String, Int]()
}
}
Or alternatively, use Eclipse's "New Scala object..." and use that instead of the worksheet.
To avoid the error message you are seeing, when you are working in a Eclipse Scala work sheet
wrap the Class definition and Companion class (Singleton object) in the same object
object worksheet {
class CheckSumAccumulator {
...
}
object CheckSumAccumulator {
...
}
CheckSumAccumulator.calculate("foobar")
}