Revamp the rabit implementation. (#10112)

This PR replaces the original RABIT implementation with a new one, which has already been partially merged into XGBoost. The new one features:
- Federated learning for both CPU and GPU.
- NCCL.
- More data types.
- A unified interface for all the underlying implementations.
- Improved timeout handling for both tracker and workers.
- Exhausted tests with metrics (fixed a couple of bugs along the way).
- A reusable tracker for Python and JVM packages.

jvm-packages/xgboost4j-flink/src/main/java/ml/dmlc/xgboost4j/java/flink/XGBoost.java

@@ -54,9 +54,9 @@ public class XGBoost {
 
     private final Map<String, Object> params;
     private final int round;
-    private final Map<String, String> workerEnvs;
+    private final Map<String, Object> workerEnvs;
 
-    public MapFunction(Map<String, Object> params, int round, Map<String, String> workerEnvs) {
+    public MapFunction(Map<String, Object> params, int round, Map<String, Object> workerEnvs) {
       this.params = params;
       this.round = round;
       this.workerEnvs = workerEnvs;
@@ -174,9 +174,9 @@ public class XGBoost {
                                    int numBoostRound) throws Exception {
     final RabitTracker tracker =
         new RabitTracker(dtrain.getExecutionEnvironment().getParallelism());
-    if (tracker.start(0L)) {
+    if (tracker.start()) {
       return dtrain
-        .mapPartition(new MapFunction(params, numBoostRound, tracker.getWorkerEnvs()))
+        .mapPartition(new MapFunction(params, numBoostRound, tracker.workerArgs()))
         .reduce((x, y) -> x)
         .collect()
         .get(0);