Choose Computer Science. Choose C. Choose -fsanitize=address. Choose gdb. Choose valgrind. Choose a fucking big **char, choose perorr, man, __VA_ARGS__ and Segmentation fault (core dumped).
Realize you really love STL, choose C++. Choose std::vector<int>. Choose object oriented. Choose cppreference.com, choose function overloading, choose method overriding. Choose cmake
Choose Java, implements, and extends. Choose multiple inheritance and abstract classes. Choose Runnable. Choose >3 billions. Choose ConcurrentHashMap.Choose design patterns. Choose JVM and meaningful stacktraces
java.io.FileNotFoundException: /etc/hadoop/conf/topology.table.file (No such file or directory)
at java.io.FileInputStream.open0(Native Method)
at java.io.FileInputStream.open(FileInputStream.java:195)
at java.io.FileInputStream.<init>(FileInputStream.java:138)
at java.io.FileInputStream.<init>(FileInputStream.java:93)
at org.apache.hadoop.net.TableMapping$RawTableMapping.load(TableMapping.java:103)
at org.apache.hadoop.net.TableMapping$RawTableMapping.resolve(TableMapping.java:129)
at org.apache.hadoop.net.CachedDNSToSwitchMapping.resolve(CachedDNSToSwitchMapping.java:119)
at org.apache.hadoop.yarn.util.RackResolver.coreResolve(RackResolver.java:101)
at org.apache.hadoop.yarn.util.RackResolver.resolve(RackResolver.java:81)
at org.apache.spark.scheduler.cluster.YarnScheduler.getRackForHost(YarnScheduler.scala:37)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$1.apply(TaskSchedulerImpl.scala:373)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$1.apply(TaskSchedulerImpl.scala:362)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at org.apache.spark.scheduler.TaskSchedulerImpl.resourceOffers(TaskSchedulerImpl.scala:362)
at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint$$anonfun$2.apply(CoarseGrainedSchedulerBackend.scala:248)
at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint$$anonfun$2.apply(CoarseGrainedSchedulerBackend.scala:240)
at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.org$apache$spark$scheduler$cluster$CoarseGrainedSchedulerBackend$$withLock(CoarseGrainedSchedulerBackend.scala:693)
at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint.org$apache$spark$scheduler$cluster$CoarseGrainedSchedulerBackend$DriverEndpoint$$makeOffers(CoarseGrainedSchedulerBackend.scala:240)
at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint$$anonfun$receiveAndReply$1.applyOrElse(CoarseGrainedSchedulerBackend.scala:211)
at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:105)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:205)
at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:101)
at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:221)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Choose Ocaml. Choose higher order function. Choose tail recursion. Choose BNF-notation. Choose arrow types. Choose uncurried functions. Choose partial application. Choose generic programming. Choose pattern matching.
Choose php. Choose prepared statements. Choose echo. Choose to manually upload your files using FileZilla. Choose $_GET. Choose 3 fucking ways to comment some code. Choose sane comparison operators. Choose your future. Choose computer science...
But why would I want to do a thing like that? I chose not to choose computer science. I chose somethin' else. And the reasons? There are no reasons. Who needs reasons when you've got python?