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1. Error too many arguments for method map scala update#
2. Error too many arguments for method map scala code#

Error too many arguments for method map scala code#

We could solve this problem using the code below, with map and groupBy. After loading the table rows into Scala, we wanted to create a unique Customer object for each customer, containing a Map from accounts to addresses. All of this information was in a single non-normalized table, so the same customer could have several rows in the table, one for each unique (account, address) pair. On one of our projects, we found ourselves loading customer information from a database, in which a single customer could have multiple accounts, and each account could have multiple addresses. We will now consider a more involved real-world problem. Alternately, there is foldRight, which iterates from right to left, and regular fold, which iterates in a non-deterministic order.įor situations in which we want to do folding, but we just want to use the first element of the list as our initial accumulator instead of providing one separately, we can use reduceLeft: Named arguments work with calls to Java methods, but only if the Java library in question was compiled with -parameters. printName (last 'Smith', 'john') // error: positional after named argument. Here we have used foldLeft, which iterates over the collection from left to right. When calling methods, you can label the arguments with their parameter names like so. Once the entire list has been traversed, the final accumulator result is returned as the result of the entire folding operation.Īlternately, we can use underscore notation to make this even shorter (each successive underscore represents the next argument to the anonymous function): Compilation of the following scala code generates different errors for line 9 and 10: import class Person(id: String. After each function execution, the result is submitted as the accumulator value to the next iteration. The current accumulator value is submitted as the first argument to the function, and the next element in the list is submitted as the second argument. There are two arguments to foldLeft, separated into two parameter sequences: the base starting value of the accumulator (0 in this case), and the function to be executed for each list element. We will now use the Scala function foldLeft to collapse our summation logic into one line: Fortunately, we have a shorthand option in the form of folding. This code is properly functional, but it is also bulky for such a simple operation. In fact, the classical for loop construction (e.g., for (int i = 0 i sum(0, List(4,8,15,16,23,42))

Error too many arguments for method map scala update#

Loop structures such as “while” and “for” are particularly common in imperative languages, and they are regularly used to iteratively update the value of a variable. However, it does come with a significant shift in mindset if you’re accustomed to writing imperative code with variable reassignment. Immutability has many benefits to program design: thread safety, functions without side effects, and encouraging concise compartmentalization. Scala is rooted in functional programming, which emphasizes immutability: the inability of a variable or object to change its state.