java.sql.SQLException: Protocol violation: [6, 7, 7, 7, 7, 7, 7, - oracle
I am using version Oracle Database 21c Express Edition Release 21.0.0.0.0 - Production Version 21.3.0.0.0
I am linking to remote database. But when I query the table I get the error "Protocol Violation"
java.sql.SQLException: Protocol Violation: [ 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, ] at oracle.jdbc.driver.T4CTTIfun.receive(T4CTTIfun.java:755) at oracle.jdbc.driver.T4CTTIfun.doRPC(T4CTTIfun.java:291) at oracle.jdbc.driver.T4C8Oall.doOALL(T4C8Oall.java:492) at oracle.jdbc.driver.T4CStatement.doOall8(T4CStatement.java:108) at oracle.jdbc.driver.T4CStatement.fetch(T4CStatement.java:1159) at oracle.jdbc.driver.OracleStatement.fetchMoreRows(OracleStatement.java:3759) at oracle.jdbc.driver.InsensitiveScrollableResultSet.fetchMoreRows(InsensitiveScrollableResultSet.java:821) at oracle.jdbc.driver.InsensitiveScrollableResultSet.fetchNextRows(InsensitiveScrollableResultSet.java:759) at oracle.jdbc.driver.InsensitiveScrollableResultSet.absoluteInternal(InsensitiveScrollableResultSet.java:731) at oracle.jdbc.driver.InsensitiveScrollableResultSet.next(InsensitiveScrollableResultSet.java:436) in RemoteResultSetImpl.getObjects(RemoteResultSetImpl.java:1342)
I think the error is caused by jdbc drivers. Can you help me?
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Related
java.sql.SQLException: Protocol violation: [6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 1]
I'm using Talend 6.5 to connect some Oracle DB with a few big query. Sometime (but I can't reproduce every-time), the same query crash with the following error : job.job.my_job - tOracleInput_10 Protocol violation: [6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 1] java.sql.SQLException: Protocol violation: [6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 1] at oracle.jdbc.driver.T4CTTIfun.receive(T4CTTIfun.java:527) at oracle.jdbc.driver.T4CTTIfun.doRPC(T4CTTIfun.java:227) at oracle.jdbc.driver.T4C8Oall.doOALL(T4C8Oall.java:531) I can't find anything on the web about this error and I'm ruining dry on how to solve it.
Creating a nested dictionary comprehension for year and month in python
I would like to create a nested dictionary with dict comprehension but I am getting syntax error.
years = [2016, 2017, 2018, 2019]
months = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
my_Dict = {i:{j: for j in months}, for i in years}
I am not sure how to declare this nested dict comprehension without getting a syntax error.
In this case, the correct way would be to use a dictionary with a nested list comprehension because if you use a nested dictionary, it will replace old values. The correct syntax, in this case, would be this one:
years = [2016, 2017, 2018, 2019]
months = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
my_Dict = {
year: [month for month in months] for year in years
}
print(my_Dict)
>>> {2016: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
2017: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
2018: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
2019: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]}
Made some slight changes to the code above and this works
key_years = {2016, 2017, 2018, 2019}
key_months = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}
myDict = {i:{j for j in key_months} for i in key_years}
print (myDict)
Output: {2016: {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}, 2017: {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}, 2018: {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}, 2019: {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}}
How to duplicate value of array in ruby
I have two arrays of integers, e.g. a = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] b = [7, 8, 9] I would like to repeatedly duplicate the value of 'b' to get a perfectly matching array lengths like this: a = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] b = [7, 8, 9, 7, 8, 9, 7, 8, 9, 7] We can assume that a.length > b.length
Assuming you mean a = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] b = [7, 8, 9] then you can do: b.cycle.take(a.length) #=> [7, 8, 9, 7, 8, 9, 7, 8, 9, 7] <script src="//repl.it/embed/JJ3x/2.js"></script> See Array#cycle and Enumerable#take for more details.
I would have used Array#cycle had it been available, but since it was taken I thought I'd suggest some alternatives (the first being my fav).
a = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
b = [7, 8, 9]
[*b*(a.size/b.size), *b[0, a.size % b.size]]
#=> [7, 8, 9, 7, 8, 9, 7, 8, 9, 7]
Array.new(a.size) { |i| b[i % b.size] }
#=> [7, 8, 9, 7, 8, 9, 7, 8, 9, 7]
b.values_at(*(0..a.size-1).map { |i| i % b.size })
#=> [7, 8, 9, 7, 8, 9, 7, 8, 9, 7]
python appending issues, function keeps changing values of list
I was trying to visualize bubblesort by making an animated plot on some unsorted list, say np.random.permutation(10) so naturally I would append the list every time it's altered within the bubblesort function until it's completely sorted. Here's the code def bubblesort(A): instant = [] for i in range(len(A)-1): lindex=0 while lindex+1<len(A): if A[lindex]> A[lindex+1]: swap(A,lindex,lindex+1) lindex+=1 else: lindex+=1 instant.append(A) return instant The problem is though, instant only returns [array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])] which is obviously not right. What has gone wrong? Thanks!
A is being operated on in-place, and bubblesort is returning a list of references to this array. Notice that if you check A now, it is also sorted. Changing if A[lindex]> A[lindex+1]: swap(A,lindex,lindex+1) to if A[lindex]> A[lindex+1]: A = A.copy() swap(A,lindex,lindex+1) making a copy before changing anything, should show the progress of the sort.
Performance analysis of openmp code (parallel) vs serial code
How do I compare the performance of parallel code(using OpenMP) vs serial code? I am using the following method
int arr[1000] = {1, 6, 1, 3, 1, 9, 7, 3, 2, 0, 5, 0, 8, 9, 8, 4, 4, 4, 0, 9, 6, 5, 9, 5, 9, 2, 5, 8, 6, 1, 0, 7, 7, 3, 2, 8, 3, 2, 3, 7, 2, 0, 7, 2, 9, 5, 8, 6, 2, 8, 5, 8, 5, 6, 3, 5, 8, 1, 3, 7, 2, 6, 6, 2, 1, 9, 0, 6, 1, 6, 3, 5, 6, 3, 0, 8, 0, 8, 4, 2, 7, 1, 0, 2, 7, 6, 9, 7, 7, 5, 4, 9, 3, 1, 1, 4, 2, 4, 1, 5, 2, 6, 0, 8, 9, 2, 6, 0, 1, 0, 2, 0, 3, 3, 4, 0, 1, 4, 8, 8, 1, 4, 9, 4, 7, 3, 8, 9, 9, 1, 4, 1, 8, 7, 9, 9, 9, 8, 9, 0, 0, 4, 2, 4, 9, 7, 6, 0, 3, 4, 8, 6, 1, 9, 0, 8, 2, 0, 8, 1, 2, 4, 2, 2, 1, 4, 1, 1, 4, 3, 3, 4, 9, 8, 0, 8, 7, 7, 8, 0, 3, 8, 8, 4, 7, 8, 5, 2, 0, 3, 3, 4, 9, 8, 6, 1, 4, 0, 4, 8, 5, 9, 4, 4, 7, 5, 2, 4, 2, 2, 6, 5, 2, 4, 2, 1, 4, 7, 3, 5, 2, 7, 9, 1, 7, 8, 4, 3, 0, 8, 1, 5, 8, 7, 1, 7, 2, 5, 2, 6, 9, 8, 2, 1, 5, 4, 2, 9, 1, 6, 6, 5, 5, 8, 6, 4, 6, 1, 7, 8, 1, 0, 3, 9, 7, 6, 7, 2, 1, 1, 8, 2, 9, 2, 3, 6, 8, 7, 8, 9, 5, 4, 4, 2, 2, 3, 6, 8, 4, 5, 6, 5, 7, 1, 7, 7, 9, 6, 9, 2, 7, 9, 4, 8, 2, 7, 5, 0, 7, 3, 2, 2, 9, 8, 7, 2, 3, 5, 2, 9, 1, 1, 5, 8, 4, 4, 5, 4, 0, 6, 6, 9, 8, 1, 7, 0, 0, 4, 2, 7, 9, 6, 2, 9, 7, 9, 1, 0, 4, 3, 0, 7, 6, 7, 8, 1, 1, 5, 5, 3, 4, 3, 2, 2, 4, 1, 2, 7, 6, 6, 4, 5, 3, 8, 4, 2, 9, 7, 2, 6, 3, 4, 3, 9, 1, 1, 0, 4, 9, 5, 7, 3, 9, 1, 5, 5, 5, 9, 2, 3, 5, 9, 8, 0, 9, 5, 2, 9, 4, 7, 5, 7, 1, 0, 7, 5, 4, 7, 9, 3, 5, 9, 8, 6, 2, 3, 1, 7, 2, 6, 0, 9, 7, 1, 2, 6, 8, 4, 5, 2, 3, 2, 2, 7, 3, 9, 2, 9, 6, 3, 2, 3, 2, 2, 9, 7, 5, 3, 4, 9, 9, 7, 8, 6, 0, 0, 4, 0, 7, 2, 4, 0, 4, 6, 9, 9, 5, 1, 0, 4, 5, 4, 7, 9, 6, 9, 6, 1, 2, 3, 0, 3, 2, 1, 1, 4, 1, 5, 4, 0, 7, 8, 3, 4, 5, 2, 5, 2, 6, 6, 6, 1, 0, 6, 2, 9, 5, 1, 0, 9, 6, 3, 4, 8, 4, 5, 2, 7, 2, 8, 8, 2, 6, 1, 6, 3, 5, 3, 6, 1, 1, 4, 4, 2, 0, 7, 1, 7, 0, 3, 8, 6, 6, 2, 6, 2, 7, 0, 0, 2, 8, 0, 4, 6, 3, 2, 0, 8, 5, 8, 2, 7, 2, 6, 1, 5, 5, 4, 4, 5, 9, 3, 3, 8, 7, 9, 0, 7, 1, 2, 9, 1, 2, 3, 8, 7, 5, 0, 8, 0, 8, 0, 9, 2, 6, 0, 7, 2, 6, 4, 9, 6, 7, 3, 4, 6, 4, 6, 3, 6, 9, 2, 7, 3, 5, 7, 1, 2, 7, 9, 5, 7, 1, 4, 0, 7, 7, 9, 1, 3, 3, 1, 1, 2, 4, 5, 9, 0, 4, 4, 6, 3, 7, 6, 8, 4, 3, 1, 7, 1, 2, 2, 8, 3, 6, 0, 1, 5, 0, 2, 1, 5, 5, 2, 0, 9, 0, 1, 0, 4, 5, 8, 7, 2, 4, 7, 7, 0, 9, 6, 1, 1, 8, 1, 5, 6, 4, 8, 2, 4, 0, 3, 1, 6, 5, 1, 7, 7, 4, 9, 1, 0, 0, 0, 4, 6, 8, 3, 6, 7, 9, 9, 0, 9, 3, 5, 6, 7, 3, 8, 3, 6, 3, 4, 4, 0, 8, 1, 8, 2, 3, 1, 4, 3, 2, 9, 1, 0, 4, 8, 9, 4, 9, 9, 3, 2, 7, 1, 9, 0, 1, 4, 8, 4, 9, 2, 7, 9, 6, 5, 1, 1, 6, 8, 4, 0, 9, 7, 2, 3, 5, 1, 9, 7, 3, 5, 9, 0, 6, 1, 2, 8, 5, 1, 4, 6, 5, 1, 5, 3, 8, 9, 4, 7, 7, 0, 9, 6, 8, 2, 9, 3, 5, 9, 2, 8, 4, 2, 0, 2, 5, 3, 2, 2, 6, 7, 9, 3, 0, 6, 7, 1, 5, 1, 0, 2, 2, 9, 0, 2, 1, 2, 7, 7, 3, 0, 7, 9, 4, 8, 1, 9, 3, 4, 1, 1, 3, 2, 6, 3, 9, 3, 6, 6, 7, 6, 1, 1, 6, 1, 3, 9, 3, 2, 6, 8, 2, 6, 7, 6, 4, 1, 5, 9, 5, 9, 2, 0, 3, 8, 5, 2, 4, 2, 9, 3, 8, 0, 6, 6, 3, 1, 6, 9, 3, 2, 7, 6, 0, 7, 2, 6, 8, 0, 5, 5, 9, 9, 5, 4, 8, 0, 7, 4, 2, 8, 9, 3, 0, 5, 9, 3, 6, 5, 4, 9, 0, 2, 7, 2, 9, 0, 9, 9, 2, 6, 4, 3, 6, 9, 7, 6, 1, 6, 0, 6, 4, 9, 9, 6, 6, 0, 2, 2, 6, 6, 3, 8, 8, 1, 0, 9, 3, 9, 8, 5, 6, 4, 8, 4, 3, 5, 0, 7, 2, 2, 3, 8, 3, 2, 5, 9, 2, 7, 1, 0, 5, 6, 0, 4};
clock_t begin, end;
double time_spent;
begin = clock();
/* here, do your time-consuming job */
#pragma omp parallel for private(temp)
for(j=0;j<1000;j++){
temp = arr[j];
for(i=0;i<temp;temp--)
result[j]=result[j]*temp;
}
end = clock();
time_spent = (double)(end - begin) / CLOCKS_PER_SEC;
printf("\n\n%f",time_spent);
But every time I run the code I get a different output. I want to see how the performance of the code differs for openmp and serial code. What method I should use to achieve the same?
The time the code takes to run will change a little bit due to computer/server usage; however, if you run both the parallel and serial versions you should see a difference in the amount of run time between the two. Also, the size of your parallel operation is pretty small. But you should see and improvement.
int arr[1000] = {1, 6, 1, 3, 1, 9, 7, 3, 2, 0, 5, 0, 8, 9, 8, 4, 4, 4, 0, 9, 6, 5, 9, 5, 9, 2, 5, 8, 6, 1, 0, 7, 7, 3, 2, 8, 3, 2, 3, 7, 2, 0, 7, 2, 9, 5, 8, 6, 2, 8, 5, 8, 5, 6, 3, 5, 8, 1, 3, 7, 2, 6, 6, 2, 1, 9, 0, 6, 1, 6, 3, 5, 6, 3, 0, 8, 0, 8, 4, 2, 7, 1, 0, 2, 7, 6, 9, 7, 7, 5, 4, 9, 3, 1, 1, 4, 2, 4, 1, 5, 2, 6, 0, 8, 9, 2, 6, 0, 1, 0, 2, 0, 3, 3, 4, 0, 1, 4, 8, 8, 1, 4, 9, 4, 7, 3, 8, 9, 9, 1, 4, 1, 8, 7, 9, 9, 9, 8, 9, 0, 0, 4, 2, 4, 9, 7, 6, 0, 3, 4, 8, 6, 1, 9, 0, 8, 2, 0, 8, 1, 2, 4, 2, 2, 1, 4, 1, 1, 4, 3, 3, 4, 9, 8, 0, 8, 7, 7, 8, 0, 3, 8, 8, 4, 7, 8, 5, 2, 0, 3, 3, 4, 9, 8, 6, 1, 4, 0, 4, 8, 5, 9, 4, 4, 7, 5, 2, 4, 2, 2, 6, 5, 2, 4, 2, 1, 4, 7, 3, 5, 2, 7, 9, 1, 7, 8, 4, 3, 0, 8, 1, 5, 8, 7, 1, 7, 2, 5, 2, 6, 9, 8, 2, 1, 5, 4, 2, 9, 1, 6, 6, 5, 5, 8, 6, 4, 6, 1, 7, 8, 1, 0, 3, 9, 7, 6, 7, 2, 1, 1, 8, 2, 9, 2, 3, 6, 8, 7, 8, 9, 5, 4, 4, 2, 2, 3, 6, 8, 4, 5, 6, 5, 7, 1, 7, 7, 9, 6, 9, 2, 7, 9, 4, 8, 2, 7, 5, 0, 7, 3, 2, 2, 9, 8, 7, 2, 3, 5, 2, 9, 1, 1, 5, 8, 4, 4, 5, 4, 0, 6, 6, 9, 8, 1, 7, 0, 0, 4, 2, 7, 9, 6, 2, 9, 7, 9, 1, 0, 4, 3, 0, 7, 6, 7, 8, 1, 1, 5, 5, 3, 4, 3, 2, 2, 4, 1, 2, 7, 6, 6, 4, 5, 3, 8, 4, 2, 9, 7, 2, 6, 3, 4, 3, 9, 1, 1, 0, 4, 9, 5, 7, 3, 9, 1, 5, 5, 5, 9, 2, 3, 5, 9, 8, 0, 9, 5, 2, 9, 4, 7, 5, 7, 1, 0, 7, 5, 4, 7, 9, 3, 5, 9, 8, 6, 2, 3, 1, 7, 2, 6, 0, 9, 7, 1, 2, 6, 8, 4, 5, 2, 3, 2, 2, 7, 3, 9, 2, 9, 6, 3, 2, 3, 2, 2, 9, 7, 5, 3, 4, 9, 9, 7, 8, 6, 0, 0, 4, 0, 7, 2, 4, 0, 4, 6, 9, 9, 5, 1, 0, 4, 5, 4, 7, 9, 6, 9, 6, 1, 2, 3, 0, 3, 2, 1, 1, 4, 1, 5, 4, 0, 7, 8, 3, 4, 5, 2, 5, 2, 6, 6, 6, 1, 0, 6, 2, 9, 5, 1, 0, 9, 6, 3, 4, 8, 4, 5, 2, 7, 2, 8, 8, 2, 6, 1, 6, 3, 5, 3, 6, 1, 1, 4, 4, 2, 0, 7, 1, 7, 0, 3, 8, 6, 6, 2, 6, 2, 7, 0, 0, 2, 8, 0, 4, 6, 3, 2, 0, 8, 5, 8, 2, 7, 2, 6, 1, 5, 5, 4, 4, 5, 9, 3, 3, 8, 7, 9, 0, 7, 1, 2, 9, 1, 2, 3, 8, 7, 5, 0, 8, 0, 8, 0, 9, 2, 6, 0, 7, 2, 6, 4, 9, 6, 7, 3, 4, 6, 4, 6, 3, 6, 9, 2, 7, 3, 5, 7, 1, 2, 7, 9, 5, 7, 1, 4, 0, 7, 7, 9, 1, 3, 3, 1, 1, 2, 4, 5, 9, 0, 4, 4, 6, 3, 7, 6, 8, 4, 3, 1, 7, 1, 2, 2, 8, 3, 6, 0, 1, 5, 0, 2, 1, 5, 5, 2, 0, 9, 0, 1, 0, 4, 5, 8, 7, 2, 4, 7, 7, 0, 9, 6, 1, 1, 8, 1, 5, 6, 4, 8, 2, 4, 0, 3, 1, 6, 5, 1, 7, 7, 4, 9, 1, 0, 0, 0, 4, 6, 8, 3, 6, 7, 9, 9, 0, 9, 3, 5, 6, 7, 3, 8, 3, 6, 3, 4, 4, 0, 8, 1, 8, 2, 3, 1, 4, 3, 2, 9, 1, 0, 4, 8, 9, 4, 9, 9, 3, 2, 7, 1, 9, 0, 1, 4, 8, 4, 9, 2, 7, 9, 6, 5, 1, 1, 6, 8, 4, 0, 9, 7, 2, 3, 5, 1, 9, 7, 3, 5, 9, 0, 6, 1, 2, 8, 5, 1, 4, 6, 5, 1, 5, 3, 8, 9, 4, 7, 7, 0, 9, 6, 8, 2, 9, 3, 5, 9, 2, 8, 4, 2, 0, 2, 5, 3, 2, 2, 6, 7, 9, 3, 0, 6, 7, 1, 5, 1, 0, 2, 2, 9, 0, 2, 1, 2, 7, 7, 3, 0, 7, 9, 4, 8, 1, 9, 3, 4, 1, 1, 3, 2, 6, 3, 9, 3, 6, 6, 7, 6, 1, 1, 6, 1, 3, 9, 3, 2, 6, 8, 2, 6, 7, 6, 4, 1, 5, 9, 5, 9, 2, 0, 3, 8, 5, 2, 4, 2, 9, 3, 8, 0, 6, 6, 3, 1, 6, 9, 3, 2, 7, 6, 0, 7, 2, 6, 8, 0, 5, 5, 9, 9, 5, 4, 8, 0, 7, 4, 2, 8, 9, 3, 0, 5, 9, 3, 6, 5, 4, 9, 0, 2, 7, 2, 9, 0, 9, 9, 2, 6, 4, 3, 6, 9, 7, 6, 1, 6, 0, 6, 4, 9, 9, 6, 6, 0, 2, 2, 6, 6, 3, 8, 8, 1, 0, 9, 3, 9, 8, 5, 6, 4, 8, 4, 3, 5, 0, 7, 2, 2, 3, 8, 3, 2, 5, 9, 2, 7, 1, 0, 5, 6, 0, 4};
clock_t begin, end;
double time_spent_omp;
double time_spent;
begin = omp_get_wtime();
/* here, do your time-consuming job */
#pragma omp parallel for private(temp)
for(j=0;j<1000;j++){
temp = arr[j];
for(i=0;i<temp;temp--)
result[j]=result[j]*temp;
}
end = omp_get_wtime();
time_spent_omp = (double)(end - begin) / CLOCKS_PER_SEC;
begin = omp_get_wtime();
/* here, do your time-consuming job */
for(j=0;j<1000;j++){
temp = arr[j];
for(i=0;i<temp;temp--)
result[j]=result[j]*temp;
}
end = omp_get_wtime();
time_spent = (double)(end - begin) / CLOCKS_PER_SEC;
printf("\n\n Time to process: %f --- Time to process with OPENMP %f",time_spent, time_spent_omp);
This should give you a better idea about how it is working.