1:14 p.m.
Hello,
For Hawkular Metrics the speed of writes is always more important than the
speed of reads (due to a variety of reasons). But that only works up to a
certain extent, in the sense that we cannot totally neglect the read part.
Let me see if I can narrow the impact of your proposal ...
You made a very good point that the performance of reads is not affected if
we discard metrics_idx for endpoints that require the metrics id. We only
need to consider the impact of querying for metrics and tenants since both
use metrics_idx. Querying the list of tenants is not very important because
it is an admin feature that we will soon secure via the newly proposed
"admin framework". So only querying for metrics definitions will be truly
affected by removing the metrics_idx completely. But only a portion of
those requests are affected because tags queries use the tags index.
To conclude, metrics_idx is only important in cases where the user wants a
full list of all metrics ever stored for a tenant id. If we can profile the
performance impact on a larger set of metric definitions and we find the
time difference without the metrics_idx is negligible then we should go
forward with your proposal.
John Sanda, do you foresee using metrics_idx in the context of metric
aggregation and the job scheduling framework that you've been working on?
Micke, what do you think are the next steps to move forward with your
proposal?
Thank you,
Stefan Negrea
On Thu, Jun 30, 2016 at 8:46 AM, Michael Burman <miburman(a)redhat.com> wrote:
Hi,
This sparked my interest after the discussions in PR #523 (adding cache to
avoid metrics_idx writes). Stefan commented that he still wants to write to
this table to keep metrics available instantly, jsanda wants to write them
asynchronously. Maybe we should instead just stop writing there?
Why? We do the same thing in tenants also at this time, we don't write
there if someone writes a metric to a new tenant. We fetch the partition
keys from metrics_idx table. Now, the same ideology could be applied to the
metrics_idx writing, read the partition keys from data. There's a small
performance penalty, but the main thing is that we don't really need that
information often - in most use cases never.
If we want to search something with for example tags, we search it with
tags - that metricId has been manually added to the metrics_idx table. No
need to know if there's metrics which were not initialized. This should be
the preferred way of doing things in any case - use tags instead of pushing
metadata to the metricId.
If we need to find out if id exists, fetching that from the PK
(PartitionKey) index is fast. The only place where we could slow down is if
there's lots of tenants with lots of metricIds each and we want to fetch
all the metricIds of a single tenant. In that case the fetching of
definitions could slow down. How often do users fetch all the tenant
metricIds without any filtering? And how performance critical is this sort
of behavior? And what use case does list of ids serve (without any
information associated to them) ?
If you need to fetch datapoints from a known metricId, there's no need for
metrics_idx table writing or reading. So this index writing only applies to
listing metrics.
- Micke
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