True, and that is a requirement I’ve heard a lot (standard views or field sets in shared sets of saved search for example). That would definitely rule out sticking with the current approach (browser local storage, per Casey’s suggestion below).
That said, I’m not sure that changes my views on RDBMS. There is an argument that a single query from RDBMS could return a set of group prefs with a user overlay, but that’s not that much better than pulling groups and overwriting the maps clientside with user, from the key value store. We’re not talking about huge amounts of preference data here. I could be swayed the other way if we were to use the RDBMS as a canonical store for user and group information (we use it for users right now, in a really not great way) but I would much rather see us plugin to the Hadoop ecosystem and use something like Ranger to sync users, or an LDAP source directly for user and group data, because I suspect no one wants to have to administer a separate user database for Metron and open up the result IAM security hole we currently have (on that, let’s at least stop storing plain text passwords!) /rant. If anything I would like to see the current RDBMS dependency come out to reduce the overall complexity, unless we have a use case that genuinely benefits from a normalised data structure, or from SQL access patterns. In short, I would still go with LDAP / Ranger or users and groups, and instead of adding an RDBMS, using group prefs and user prefs in the existing KV store (HBase) to reduce the operational maintenance burden on the platform. Simon > On 2 Feb 2018, at 12:50, Otto Fowler <ottobackwa...@gmail.com> wrote: > > It is not uncommon to want to have ‘shared’ preferences or setups. Think of > shared dashboards or queries vs. personal version in jira. Would RDBMS help > with that? > > > > On February 2, 2018 at 07:17:04, Simon Elliston Ball > (si...@simonellistonball.com <mailto:si...@simonellistonball.com>) wrote: > >> Introducing a RDBMS to the stack seems unnecessary for this. >> >> If we consider the data access patterns for user profiles, we are unlikely >> to query into them, or indeed do anything other than look them up, or write >> them out by a username key. To that end, using an ORM to translate a a >> nested config object into a load of tables seems to introduce complexity and >> brittleness we then have to take away through relying on relational >> consistency models. We would also end up with, as Mike points out, a whole >> new disk deployment patterns and a bunch of additional DBA ops process >> requirements for every install. >> >> Since the access pattern is almost entirely key => value, hbase seems a good >> option (because we already have it there, it would be kinda crazy at this >> scale if we didn’t already have it) or arguably zookeeper, but that might be >> at the other end of the scale argument. I’d even go as far as to suggest >> files on HDFS to keep it simple. >> >> Simon >> >> > On 1 Feb 2018, at 23:24, Michael Miklavcic <michael.miklav...@gmail.com >> > <mailto:michael.miklav...@gmail.com>> wrote: >> > >> > Personally, I'd be in favor of something like Maria DB as an open source >> > repo. Or any other ansi sql store. On the positive side, it should mesh >> > seamlessly with ORM tools. And the schema for this should be pretty >> > vanilla, I'd imagine. I might even consider skipping ORM for straight JDBC >> > and simple command scripts in Java for something this small. I'm not >> > worried so much about migrations of this sort. Large scale DBs can get >> > involved with major schema changes, but thats usually when the datastore >> > is >> > a massive set of tables with complex relationships, at least in my >> > experience. >> > >> > We could also use hbase, which probably wouldn't be that hard either, but >> > there may be more boilerplate to write for the client as compared to >> > standard SQL. But I'm assuming we could reuse a fair amount of existing >> > code from our enrichments. One additional reason in favor of hbase might >> > be >> > data replication. For a SQL instance we'd probably recommend a RAID store >> > or backup procedure, but we get that pretty easy with hbase too. >> > >> > On Feb 1, 2018 2:45 PM, "Casey Stella" <ceste...@gmail.com >> > <mailto:ceste...@gmail.com>> wrote: >> > >> >> So, I'll answer your question with some questions: >> >> >> >> - No matter the data store we use upgrading will take some care, right? >> >> - Do we currently depend on a RDBMS anywhere? I want to say that we do >> >> in the REST layer already, right? >> >> - If we don't use a RDBMs, what's the other option? What are the pros >> >> and cons? >> >> - Have we considered non-server offline persistent solutions (e.g. >> >> https://www.html5rocks.com/en/features/storage >> >> <https://www.html5rocks.com/en/features/storage>)? >> >> >> >> >> >> >> >> On Thu, Feb 1, 2018 at 9:11 AM, Ryan Merriman <merrim...@gmail.com >> >> <mailto:merrim...@gmail.com>> wrote: >> >> >> >>> There is currently a PR up for review that allows a user to configure >> >>> and >> >>> save the list of facet fields that appear in the left column of the >> >> Alerts >> >>> UI: https://github.com/apache/metron/pull/853 >> >>> <https://github.com/apache/metron/pull/853>. The REST layer has ORM >> >>> support which means we can store those in a relational database. >> >>> >> >>> However I'm not 100% sure this is the best place to keep this. As we add >> >>> more use cases like this the backing tables in the RDBMS will need to be >> >>> managed. This could make upgrading more tedious and error-prone. Is >> >> there >> >>> are a better way to store this, assuming we can leverage a component >> >> that's >> >>> already included in our stack? >> >>> >> >>> Ryan >> >>> >> >>