How to leverage search (find) capability using Parking Lot?

Searching using the parking lot

A little known feature of the parking lot is that it is possible to paste data in to it as a way of searching for nodes in the dataset using the paste functionality. This can be preferable to using the search box when writing out the search term becomes too cumbersome.

An example of when this is the case would be if I had the names of 500 people that I wanted to find in a 10000 node dataset – performing this with a search expression would be infeasible (imagine typing 500 names into the search pane!).

Below I detail how to use the parking lot method for searching, using a small dataset example. It is important to understand that the power of this method comes through in larger datasets, when looking for many nodes that can only be categorised by a large number of buckets (e.g. name).

Take this sample dataset:

Suppose I want to find nodes whose department is Finance.

I raise the paste dialog by clicking the  button in the parking lot section of the side bar.

Then pasting the following:

Department

Finance

Into the dialog will populate the parking lot with these Finance nodes:

Assume after each example that I clear the parking lot unless stated otherwise.

Suppose I want to find nodes that are either Finance or Operations.  Then I would paste the following:

Department

Finance

Operations

Which populates the parking lot with all Finance and Operations nodes:

This is useful for searching for names in a dataset (as in the introduction paragraph).  Suppose I have a list of names of people I want to find in the dataset:

I can find nodes with these names that are contained in the dataset by pasting this list into the parking lot.

Suppose we want to search for nodes using more than one condition (as per in the filter control).  To find any Finance nodes that are also in the UK or are in France, I would paste in:

Which returns all nodes that satisfy this condition:

Suppose I wanted to find all nodes that have Department Operations and Location Portugal AND all nodes that have Department Finance and Location UK.

The temptation might be to paste in:

However, this returns nodes that have both Department Operations OR Finance AND are in Portugal OR the UK.  We see in the results that James is present despite having Department Finance and Location Portugal.

To do this we need to paste in:

Which gives:

And then paste:

To give:

The takeaway from this example is that successive pastes stack, so we can build complex searches in this way.

This article was authored by Tom Simpkins from the OrgVue Development Team