scala

问题 I'm trying to deal with an ambiguous implicits problem, and (relatedly) figure out what best practise should be for parameterizing typeclasses. I have a situation where I am using a typeclass to implement a polymorphic method. I initially tried the approach below: abstract class IsValidTypeForContainer[A] object IsValidTypeForContainer { implicit val IntIsValid = new IsValidTypeForContainer[Int] {} implicit val DoubleIsValid = new IsValidTypeForContainer[Double] {} } abstract class

问题 I have a class PluginManager which accepts a Set<Plugin> using the Guice multi-bindings feature. However, the PluginManager has some runtime information that needs to be passed to the Plugin constructor. This seems to be a perfect use-case for Guice assisted injection i.e. my PluginManager would have Set<PluginFactory> injected, where the runtime information is provided to each factory, resulting in the required Plugin instances. I don't know the syntax to use in the Module however. The

问题 I have a csv file zipped in bz2 format, like unix/linux do we have any single line command to extrac/decompress the file file.csv.bz2 to file.csv in spark-scala? 回答1: You can use built in function in SparkContext(sc), this worked for me sc.textFile("file.csv.bz2").saveAsTextFile("file.csv") 来源： https://stackoverflow.com/questions/52981195/how-to-extract-a-bz2-file-in-spark

问题 I have a method that writes one of my classes Foo , which is defined as Thrift, in Parquet form. import Foo import org.apache.spark.rdd.RDD import org.apache.thrift.TBase import org.apache.hadoop.mapreduce.Job import org.apache.parquet.hadoop.ParquetOutputFormat import org.apache.parquet.hadoop.thrift.ParquetThriftOutputFormat def writeThriftParquet(rdd: RDD[Foo], outputPath: String): Unit = { val job = Job.getInstance() ParquetThriftOutputFormat.setThriftClass(job, classOf[Foo])

问题 I have a dataframe with columns col1,col2,col3. col1,col2 are strings. col3 is a Map[String,String] defined below |-- col3: map (nullable = true) | |-- key: string | |-- value: string (valueContainsNull = true) I have grouped by col1,col2 and aggregated using collect_list to get an Array of Maps and stored in col4. df.groupBy($"col1", $"col2").agg(collect_list($"col3").as("col4")) |-- col4: array (nullable = true) | |-- element: map (containsNull = true) | | |-- key: string | | |-- value:

问题 Abstract member method is illegal in a singleton object scala> object Foo { | def g: Int | } def g: Int ^ On line 2: error: only traits and abstract classes can have declared but undefined members as is abstract value member scala> object Foo { | val x: Int | } val x: Int ^ On line 2: error: only traits and abstract classes can have declared but undefined members however abstract type member is legal in a singleton object scala> object Foo { | type A | } object Foo so clearly the sense in

问题 Abstract member method is illegal in a singleton object scala> object Foo { | def g: Int | } def g: Int ^ On line 2: error: only traits and abstract classes can have declared but undefined members as is abstract value member scala> object Foo { | val x: Int | } val x: Int ^ On line 2: error: only traits and abstract classes can have declared but undefined members however abstract type member is legal in a singleton object scala> object Foo { | type A | } object Foo so clearly the sense in

问题 I have List[N] like below val check = List ("a","b","c","d") where N can be any number of elements. I have a dataframe with only column called "value". Based on the contents of value i need to create N columns with column names as elements in the list and column contents as substring(x,y) I have tried all possible ways, like withColumn , selectExpr , nothing works. Please consider substring(X,Y) where X and Y as some numbers based on some metadata Below are my different codes which I tried,

问题 I have List[N] like below val check = List ("a","b","c","d") where N can be any number of elements. I have a dataframe with only column called "value". Based on the contents of value i need to create N columns with column names as elements in the list and column contents as substring(x,y) I have tried all possible ways, like withColumn , selectExpr , nothing works. Please consider substring(X,Y) where X and Y as some numbers based on some metadata Below are my different codes which I tried,

问题 I have a dataframe with a key column and a column which has an array of struct. The Schema looks like below. root |-- id: string (nullable = true) |-- desc: array (nullable = false) | |-- element: struct (containsNull = true) | | |-- name: string (nullable = true) | | |-- age: long (nullable = false) The array "desc" can have any number of null values. I would like to create a final dataframe with the array having none of the null values using spark 1.6: An example would be: Key . Value 1010