pfilter | Basic Python particle filter | Data Manipulation library

It is done in parallel, but there are several points explaining why it is longer using parallel in your test, that I will try to explain.

First, your test is not really accurate because:

• The 2 processes (1 single threaded, and 1 parallel) are executed in parallel. If you want your result to be more precise, you should run one after the other
• You should execute the test at least 2 times, because the first time several things are not yet initialized, so the timing take into account class loading, schedulers initialization, etc... and we should not take them into account when comparing the 2 solutions.

But that not the most important point. Actually processing the filter in parallel is requesting much more work behind the scene, to split the data and dispatch it to the different threads. So because the predicate in your filter is very simple (only a comparison), at the end it is more efficient to do it in one shot in a single thread instead of doing it in a parallel way. The parallel way will become more efficient if the processing time of the filter is more important, because this processing time will be (more or less) divided by the number of parallel threads.

I rewrite your test to illustrate those points:

• I run the test 2 times to avoid to take the initialization into account in the timing
• I wait for the single threaded test to finish before to launch the parallel one, so they cannot interfer
• Finally, I test with a very simple predicate (as in your test), and a predicate that is longer (I just put a sleep to simulate a longer processing). Note that I reduce the number of items in the longer predicate to have the result faster.

Here is the code:

If I set Beta=100 in the code above I can get a negative-infinite log-likelihood.

Replacing the measurement-error snippet with this:

I found the answer here: Webmasters API User does not have sufficient permission for site (MartijnvdB's answer in case the deep link to the specific answer breaks).

I needed to change this:

Below should work. Please have a try:

expression="count(//Pnode[not (@PFilter='1')][Child1/Child2[@Filter='1']])"

Or

expression="count(//Doc1/Pnode[not (@PFilter='1')][Child1/Child2[@Filter='1']])"

Solution:

The Solution is that you nest BasicDBObjects in BasicDBObjects.

Since your identifier has a space in it, you need to quote it.

pfilter: "[*].{\"Ping response\": stdout_lines}"

To ease the writing/readability, you can use a yaml folded block scalar and remove one level of quote escaping: