TuneHyperparameters - Exception thrown in awaitResult

@imatiach-msft is already working on this.

Since Aug 26, 2019.

[log4j.txt](https://github.com/Azure/mmlspark/files/3539284/log4j.txt)

Following this example: https://github.com/Azure/mmlspark/blob/master/notebooks/samples/HyperParameterTuning%20-%20Fighting%20Breast%20Cancer.ipynb

```
from mmlspark.automl import TuneHyperparameters
from mmlspark.train import TrainClassifier
from pyspark.ml.classification import LogisticRegression, RandomForestClassifier, GBTClassifier
logReg = LogisticRegression()
randForest = RandomForestClassifier()
smlmodels = [logReg, randForest]

from mmlspark.automl import *

paramBuilder = \
HyperparamBuilder() \
.addHyperparam(logReg, logReg.regParam, RangeHyperParam(0.1, 0.3)) \
.addHyperparam(randForest, randForest.numTrees, DiscreteHyperParam([5,10])) \

searchSpace = paramBuilder.build()
# The search space is a list of params to tuples of estimator and hyperparam
print(searchSpace)
randomSpace = RandomSpace(searchSpace)

bestModel = TuneHyperparameters(
evaluationMetric="accuracy", models=smlmodels, numFolds=1,
numRuns=len(smlmodels) * 1, parallelism=1,
paramSpace=randomSpace.space(), seed=0).fit(data.select("features", "label"))
```

Setting numFolds etc. larger simply increases the time to throw an exception.

The data is in a PySpark style format. A huge feature vector + a ValueIndexed label. Hence I do not call TrainClassifier on the models. I did attempt to use TrainClassifier (which can train a single model) but it still throws the same error.

> org.apache.spark.SparkException: Job aborted due to stage failure: Task 22 in stage 36.0 failed 4 times, most recent failure: Lost task 22.3 in stage 36.0 (TID 843, 10.179.68.7, executor 2): java.util.NoSuchElementException: key not found: 85