RDD filter in for loop gave strange results

[Marco Wong]

Dear Spark users,

I ran the Python code below on a simple RDD, but it gave strange results.
The filtered RDD contains non-existent elements which were filtered away
earlier. Any idea why this happened?
```
rdd = spark.sparkContext.parallelize([0,1,2])
for i in range(3):
    print("RDD is ", rdd.collect())
    print("Filtered RDD is ", rdd.filter(lambda x:x!=i).collect())
    rdd = rdd.filter(lambda x:x!=i)
    print("Result is ", rdd.collect())
    print()
```
which gave
```
RDD is  [0, 1, 2]
Filtered RDD is  [1, 2]
Result is  [1, 2]

RDD is  [1, 2]
Filtered RDD is  [0, 2]
Result is  [0, 2]

RDD is  [0, 2]
Filtered RDD is  [0, 1]
Result is  [0, 1]
```

Thanks,

Marco