how to test fileStream? - filestream

FileStream stream = new FileStream("test.xls", FileMode.OpenOrCreate)
ExcelWriter writer = new ExcelWriter(stream);
writer.BeginWrite();
writer.WriteCell (1, 0, "No");
writer.WriteCell (1, 1, "Status");
writer.WriteCell (1, 2, "Date");
writer.WriteCell (1, 3, "Time");
writer.WriteCell (1, 4, "Unit");
writer.WriteCell (1, 5, "Total");
writer.EndWrite();
stream.Close();
i wrote this code in button.when i first click it work.but when i click again it got error :mono system.io.ioexception sharing violation on path....how to fix it?please help.thanks

Related

Getting the first item for a tuple for each row in a list in Scala

I am looking to do this in Scala, but nothing works. In pyspark it works obviously.
from operator import itemgetter
rdd = sc.parallelize([(0, [(0,'a'), (1,'b'), (2,'c')]), (1, [(3,'x'), (5,'y'), (6,'z')])])
mapped = rdd.mapValues(lambda v: map(itemgetter(0), v))
Output
mapped.collect()
[(0, [0, 1, 2]), (1, [3, 5, 6])]

val rdd = sparkContext.parallelize(List(
(0, Array((0, "a"), (1, "b"), (2, "c"))),
(1, Array((3, "x"), (5, "y"), (6, "z")))
))
rdd
.mapValues(v => v.map(_._1))
.foreach(v=>println(v._1+"; "+v._2.toSeq.mkString(",") ))
Output:
0; 0,1,2
1; 3,5,6

Group_by_key in order in Pyspark

rrr = sc.parallelize([1, 2, 3])
fff = sc.parallelize([5, 6, 7, 8])
test = rrr.cartesian(fff)
Here's test:
[(1, 5),(1, 6),(1, 7),(1, 8),
(2, 5),(2, 6),(2, 7),(2, 8),
(3, 5),(3, 6),(3, 7),(3, 8)]
Is there a way to preserve the order after calling groupByKey:
test.groupByKey().mapValues(list).take(2)
Output is this where the list is in random order:
Out[255]: [(1, [8, 5, 6, 7]), (2, [5, 8, 6, 7]), (3, [6, 8, 7, 5])]
The desired output is:
[(1, [5,6,7,8]), (2, [5,6,7,8]), (3, [5,6,7,8])]
How to achieve this?

You can add one more mapValues to sort the lists:
result = test.groupByKey().mapValues(list).mapValues(sorted)

How to store each element to dictionary and count dictionary value with pyspark?

I want to count elements value of dictionary. I try with this code:
def f_items(data, steps=0):
items = defaultdict(int)
for element in data:
if element in data:
items[element] += 1
else:
items[element] = 1
return items.items()
data = [[1, 2, 3, 'E'], [1, 2, 3, 'E'], [5, 2, 7, 112, 'A'] ]
rdd = sc.parallelize(data)
items = rdd.flatMap(lambda data: [y for y in f_items(data)], True)
print (items.collect())
The output of this code is shown below:
[(1, 1), (2, 1), (3, 1), ('E', 1), (1, 1), (2, 1), (3, 1), ('E', 1), (5, 1), (2, 1), (7, 1), (112, 1), ('A', 1)]
But, it should show the result following:
[(1, 2), (2, 3), (3, 3), ('E', 2), (5, 1), (7, 1), (112, 1), ('A', 1)]
How to achieve this?

Your last step should be a reduceByKey function call on the items rdd.
final_items = items.reduceByKey(lambda x,y: x+y)
print (final_items.collect())
You can look into this link to see some examples of reduceByKey in scala, java and python.

Idiomatic scala solution to combining sequences

Imagine a function combineSequences: (seqs: Set[Seq[Int]])Set[Seq[Int]] that combines sequences when the last item of first sequence matches the first item of the second sequence. For example, if you have the following sequences:
(1, 2)
(2, 3)
(5, 6, 7, 8)
(8, 9, 10)
(3, 4, 10)
The result of combineSequences would be:
(5, 6, 7, 8, 8, 9, 10)
(1, 2, 2, 3, 3, 4, 10)
Because sequences 1, 2, and 5 combine together. If multiple sequences could combine to create a different result, the decisions is arbitrary. For example, if we have the sequences:
(1, 2)
(2, 3)
(2, 4)
There are two correct answers. Either:
(1, 2, 2, 3)
(2, 4)
Or:
(1, 2, 2, 4)
(2, 3)
I can only think of a very imperative and fairly opaque implementation. I'm wondering if anyone has a solution that would be more idiomatic scala. I've run into related problems a few times now.

Certainly not the most optimized solution but I've gone for readability.
def combineSequences[T]( seqs: Set[Seq[T]] ): Set[Seq[T]] = {
if ( seqs.isEmpty ) seqs
else {
val (seq1, otherSeqs) = (seqs.head, seqs.tail)
otherSeqs.find(_.headOption == seq1.lastOption) match {
case Some( seq2 ) => combineSequences( otherSeqs - seq2 + (seq1 ++ seq2) )
case None =>
otherSeqs.find(_.lastOption == seq1.headOption) match {
case Some( seq2 ) => combineSequences( otherSeqs - seq2 + (seq2 ++ seq1) )
case None => combineSequences( otherSeqs ) + seq1
}
}
}
}
REPL test:
scala> val seqs = Set(Seq(1, 2), Seq(2, 3), Seq(5, 6, 7, 8), Seq(8, 9, 10), Seq(3, 4, 10))
seqs: scala.collection.immutable.Set[Seq[Int]] = Set(List(1, 2), List(2, 3), List(8, 9, 10), List(5, 6, 7, 8), List(3, 4, 10))
scala> combineSequences( seqs )
res10: Set[Seq[Int]] = Set(List(1, 2, 2, 3, 3, 4, 10), List(5, 6, 7, 8, 8, 9, 10))
scala> val seqs = Set(Seq(1, 2), Seq(2, 3, 100), Seq(5, 6, 7, 8), Seq(8, 9, 10), Seq(100, 4, 10))
seqs: scala.collection.immutable.Set[Seq[Int]] = Set(List(100, 4, 10), List(1, 2), List(8, 9, 10), List(2, 3, 100), List(5, 6, 7, 8))
scala> combineSequences( seqs )
res11: Set[Seq[Int]] = Set(List(5, 6, 7, 8, 8, 9, 10), List(1, 2, 2, 3, 100, 100, 4, 10))

How to check if a list of matrix contains a given matrix in Maple

I have some problems in Maple.
If I have a matrix:
Matrix1 := Matrix(2, 2, {(1, 1) = 31, (1, 2) = -80, (2, 1) = -50, (2, 2) = 43});
I want to decide if it is in the below list:
MatrixList := [Matrix(2, 2, {(1, 1) = 31, (1, 2) = -80, (2, 1) = -50, (2, 2) = 43}), Matrix(2, 2, {(1, 1) = -61, (1, 2) = 77, (2, 1) = -48, (2, 2) = 9})];
I did the following:
evalb(Matrix1 in MatrixList);
but got "false".
Why? And how do I then make a program that decide if a matrix is
contained in a list of matrices.

Here's a much cheaper way than DrC's
ormap(LinearAlgebra:-Equal, MatrixList, Matrix1)