GridGain — Extreme Speed and Scale for Data-Intensive Apps
GridGain combines stream processing, a distributed in-memory data grid, and colocated compute to deliver data processing and analytics at massive scale and ultra-low latencies. GridGain combines stream processing, a distributed in-memory data grid, and colocated compute to deliver data processing and analytics at massive scale and ultra-low latencies.
The Scala Programming Language
val fruits = List("apple", "banana", "avocado", "papaya") val countsToFruits = // count how many 'a' in each fruit fruits.groupBy(fruit => fruit.count(_ == 'a')) for (count, fruits) <- countsToFruits do println(s"with 'a' × $count = $fruits") // prints: with 'a' × 1 = List(apple) // prints: with 'a' × 2 = List(avocado) // prints: with 'a' × 3 = List(banana, papaya)
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