/** * Convert this promise to a Scala future. *

* This is equivalent to FutureConverters.toScala(this), however, it converts the wrapped completion stage to * a future rather than this, which means if the wrapped completion stage itself wraps a Scala future, it will * simply return that wrapped future. * * @return A Scala future that is completed when this promise is completed. */ public

The getOrElseUpdate is useful for accessing maps that act as caches. Say you have an expensive computation triggered by invoking a function f : scala> def f(x: String) = { println("taking my time."); sleep(100) x.reverse } f: (x: String)String

Package structure . The scala package contains core types like Int, Float, Array or Option which are accessible in all Scala compilation units without explicit qualification or imports. As I understand, TrieMap.getOrElseUpdate is still not truly atomic, and this fixes only returned result (it could return different instances for different callers before this fix), so the updater function still might be called several times, as documentation (for 2.11.7) says: Note: This method will invoke op at most once. ms getOrElseUpdate (k, d) If key k is defined in map ms, return its associated value.

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You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. Customer cannot submit Spark job in InsightEdge version 15.0 with specific Kubernetes versions While testing Spark Project Hive, there are RuntimeExceptions as follows, VersionsSuite: success sanity check *** FAILED *** java.lang.RuntimeException: download Once the project is set up, go to Scala > Run Setup Diagnostics… and make sure to check the field “Use Scala-compatible JDT content assist proposals” Done. If you don’t do step 6, you will not get any suggestions when writing code, so make sure that you have completed step 6 before deciding not to continue with Eclipse. 17/01/10 19:17:20 ERROR ShuffleBlockFetcherIterator: Failed to get block(s) from bigdata-hdp-apache1828.xg01.diditaxi.com:7337 java.lang.NullPointerException: group Solved: Despite adding the following, --conf. Hey AK, Following is the stack trace: 10:13:28,194 WARN [TaskSetManager] Lost task 8.0 in stage 1.0 (TID 4, hostname GitHub Gist: instantly share code, notes, and snippets.

[Redirected to scala-language since I'm not on scala-user.] Someone asked me recently why I'm against extending Function1 casually. In this we have a pretty good example. I'm not sure why you declared the map to be an implicit val: implicit val cache = mutable.Map[Int, String]() I imagine you didn't do that with the intention of placing a competing

I have upgraded to Scala IDE 4.1 (Luna) and it seems slow to compile even after a minor file change. OS: Ubuntu Linux 18.10. Java: java version "1.8.0_201" Java(TM) SE Runtime Environment (build 1.8.0_201-b09) Java HotSpot(TM) 64-Bit Server VM (build 25.201-b09, mixed mode) Okay, so in preparation for the DataWorks Summit :: San Jose I was going over the Spark 2 cluster we give our students, you know - testing the important labs, etc. and lo and behold I found a problem: Testing my old code for Spark 2 Structured Streaming with Apache Kafka was suddenly broken with an The following examples show how to use redis.clients.jedis.Jedis.These examples are extracted from open source projects.

ms getOrElseUpdate (k, d) If key k is defined in map ms, return its associated value. Otherwise, update ms with the mapping k -> d and return d. Removals: ms -= k: Removes mapping with key k from ms as a side effect and returns ms itself. ms -= (k, l, m) Removes mappings with the given keys from ms as a side effect and returns ms itself. ms --= ks

Oct 9, 2019 ```scala private def consumeAbortedTxnsUpTo(offset: Long): Unit = { while ( abortedTransactions. getOrElseUpdate(abortedTxn.producerId  Nov 27, 2020 [source, scala]¶. compute( split: Partition, context: TaskContext): Iterator[T]. compute computes the input split spark-rdd-partitions  Jul 23, 2013 Updating a Map in Scala. Relevant references: But how can we increase the count if the word is already in the map? Using Only Built-in Methods.

Skip to content. All gists Back to GitHub Sign in Sign up Sign in Sign up {{ message }} No Spark shuffle block is larger than 2GB (Integer.MAX_VALUE bytes) therefore you need additional / smaller partitions.You should adjust spark.default.parallelism and spark.sql.shuffle.partitions (default 200) such that the number of partitions can accommodate your data without reaching the 2GB limit (you could try aiming for 256MB / partition so for 200GB you get 800 partitions). The following examples show how to use scala.collection.mutable.Set.These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. /** * Convert this promise to a Scala future. *

* This is equivalent to FutureConverters.toScala(this), however, it converts the wrapped completion stage to * a future rather than this, which means if the wrapped completion stage itself wraps a Scala future, it will * simply return that wrapped future. * * @return A Scala future that is completed when this promise is completed.
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This means it’s possible for the value to be computed multiple times if multiple threads are calling getOrElse simultaneously. * getOrElseUpdate(key, value) method that lazily evaluates the value parameter only if the key is not already present * in the cache. * * You may be asking, why not just use Scala's ConcurrentMap interface, which already has a getOrElseUpdate method?

.getOrElseUpdate makes it convenient to use a mutable Map as a cache: the second parameter to .getOrElseUpdate is a lazy "by-name" parameter, and is only evaluated when the key is not found in the Map. This provides the common "check if key present, if so return value, otherwise insert new value and return that" workflow built in.
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Spark version : 2 Steps:. install conda on all nodes (python2.7) ( pip install conda ) create requirement1.txt with "numpy > requirement1.txt "Run kmeans.py application in yarn-client mode.

UnsatisfiedLinkError: /mxnet/scala-package/init-native/linux-x86_64/target/libmxnet-init-scala getOrElseUpdate(MapLike.scala:194) [INFO] at  getOrElseUpdate(Map.scala:82) [INFO] at scala.reflect.macros.runtime.MacroRuntimes.standardMacroRuntime(MacroRuntimes.scala:50)  getOrElseUpdate$(MapLike.scala:203) [error] at scala.collection.mutable.AbstractMap.getOrElseUpdate(Map.scala:80) [error] at scala.reflect.macros.runtime. TypeAnalyzer$UDTAnalyzerInstance$UDTAnalyzerCache$$anonfun$getOrElseUpdate$2$$anonfun$apply$4.apply(TypeAnalyzer.scala:481)  getOrElseUpdate(Map.scala:80) [error] at scala.reflect.macros.runtime.MacroRuntimes.standardMacroRuntime(MacroRuntimes.scala:38)  getOrElseUpdate(Map.scala:80). [error] at scala.reflect.macros.runtime.MacroRuntimes.standardMacroRuntime(MacroRuntimes.scala:38). Jag är ny på scala. Som titel import scala.collection.mutable val map = mutable. getOrElseUpdate(100, (0, 0)) res3: (Int, Int) = (0,0) scala> googleMap res4:  Jag är helt ny på att programmera med Scala och jag har följande problem: Jag getOrElseUpdate(key, new ListBuffer()) get('Strings') += 'a' get('Strings') += 'b'  beräkna punktprodukten (skalär produkt) för två glesa vektorer i Scala. Map val Sparse1 = Map[Int, Int]() for (k <- 0 to 20) { Sparse1 getOrElseUpdate (k,  Can the highlighted with comment line be rewritten using the getOrElseUpdate method?

Scala collections provide many common operations for constructing them, Mutable Map s have a convenient getOrElseUpdate function, that allows you to look 

Have ParTrieMap throw an exception for getOrElseUpdate. retronym merged 3 commits into scala: 2.12.x from paplorinc: getOrElseUpdate Nov 22, 2016 Conversation 57 Commits 3 Checks 0 Files changed Conversation The getOrElseUpdate is useful for accessing maps that act as caches.

Resolution. Remove these request types or add at least one field to the request type. Play Framework - The High Velocity Web Framework For Java and Scala.