This feature will improve the performance of indexing resource types within Searchlight.
If the above link is too troublesome to follow, please indulge us while we plagiarize from the blueprint.
When indexing (first time or re-indexing) we will index all resource group types sequentially. We loop through all plugins, indexing each one in turn. The result is that the time it takes to re-index is equal to the sum of the time for all plugins. This may take longer than it should. In some cases a lot longer.
The time it takes to complete the full index is:
n O( ∑ T(p) ) p=0
When n is the number of plugins and T(p) is the time it takes for plugin p to index.
We should change the algorithm to index in parallel, rather than in serial. As we are looping through each plugin to re-index, we should spin each indexing task into it’s own thread. This way the time it takes to index is the time it takes the longest plugin to re-index.
With this enhancement, the time it takes to complete the index is:
n O( MAX( T(p) ) ) p=0
To provide context for the design, we will review the current design for re-indexing. A re-indexing starts when the admin runs the command:
searchlight-manage index sync
Under the cover, searchlight-manage is doing the following:
- Determine which resource groups need to be re-indexed.
- Determine which resource types within each resource group needs to be re-indexed.
- For each resource type that does need to be re-indexed, searchlight-manage will call the plugin associated with that resource type. The plugin will make API calls to that service and re-index the information.
- For each resource type that does not need to be re-indexed, searchlight-manage will call ElasticSearch directly and re-index from the old index into the new index.
- Once all re-indexing is complete, the ES aliases are adjusted and searchlight-manage returns to the user.
As described in the blueprint, we would like to reduce the time to complete the re-index. Based on discussions with the blueprint and this spec, we will be implementing only the first enhancement in the blueprint. We will be using python threads to accomplish this task. We need to understand the design issues associated with implementing a multi-thread approach.
If there are a lot of inter-dependencies within the plugins, it may not pay off to try to multi-thread the plugins. Reviewing the code and functionality of the plugins, they appear to be separate enough that they are good candidates to be moved into their own threads. The plugins are isolated from each other and do not depend on any internal structures to handle the actual indexing.
Design Proposal: The individual plugins can be successfully threaded.
The obvious candidates are the resource type (e.g. OS::Nova::Server) or the resource type group (e.g. the index “searchlight”). The main reason that we are considering this enhancement is due to the large amount of time for a particular resource type, but not for a particular resource type group.
Internal to searchlight-manage, this distinction fades rather quickly. We use the resource type groups to only determine which resource types need to be re-indexed. We also have an existing enhancement within searchlight-manage where we re-index through the plugin API only the resource types that were explicitly demanded by the user. All other resource types are re-indexed directly within ElasticSearch. We need to keep this enhancement.
Keeping the current design intact means we will want to thread on the fine resource type level and not at the gross resource type group level. Based on the parent/child relationship that exists between some of the resource types, this is the “fine” level we will be considering.
Since we are already using bulk commands for Elasticsearch re-indexing, we will place all of the Elasticsearch re-indexing into a single thread. Considering that this iwll be I/O bound on Elasticsearch’s side, There does not appear to be any advantage of doing an Elasticsearch re-indexing for each resource type in a separate thread.
Design Proposal: Whenever the indexing code currently calls the plugin API, it will create a worker in the thread pool.
Design Proposal: All of the calls to ElasticSearch to re-index an existing index, will be placed in a single worker in the thread pool.
There may be a large number of plugins used with Searchlight. If each plugin has its own thread, we may be using a lot of threads. Instead of having a single thread map to a single plugin, we will use a thread pool. This will keep the number of threads to a managable level while still allowing for an appropriate level of asynchronous re-indexing. The size of the thread pool can be changed through a configuration option.
Design Proposal: Use a thread pool.
In the serial model of re-indexing, it is trivial to know when to switch the ElasticSearch alias to the use the new index. It’s when the last index finishes! Switching over to a model of asynchronous threads running in parallel potentially complicates the alias update.
The indexing code will wait for all the threads to complete. When all threads have completed, the indexing code can continue with updating the aliases.
Design Proposal: The alias switching code will be run after all of the threads have completed.
The indexing code will need to have the threads communicate if a catastrophic failure occurred. After all workers have been placed into the Thread pool, the main program will wait for all of the threads to finish. If any thread fails, it will raise an exception. The exception will be caught and the normal clean-up call will commence. All threads that are still waiting to run will be cancelled.
Design Proposal: Catch exceptions thrown by a failing thread.
For those following along with the code (searchlight/cmd/manage.py::sync), here is a rough guide to the changes. We will reference the sections as mentioned in the large comment blocks:
We can always choose to not perform any enhancements. Or we can go back to the first draft of this spec.