1) It’s not a principal point, I can change schema. The INFORMATION_SCHEMA
was used because it’s already exists and usually used for metadata tables
and views. Your proposal is to use schema “IGNITE”, am I understand you
right? BTW, for now, we can’t query another (H2) meta tables from the
INFORMATION_SCHEMA, so, “Ignite system views” is only available views to
query from this schema.
2) Exactly for this reason the IGNITE_INSTANCE view is useful: to determine
which node we are connected to.
3) As the first phase, in my opinion, local views will be enough.
Performance and caching of distributed views should be discussed at next
phases, when distributed views implementation will be planned. In current
implementation I tried to use indexing for local views wherever it’s
possible.
4) I don’t think, that JVM info is more critical information than, for
example, caches or nodes information. When authorization capabilities
planned to implement?
About local data: yes, we can rename all currently implemented views for
the local node data as LOCAL_..., and create (someday) new whole cluster
views (which use distributed requests) without prefix or, for example, with
CLUSTER_ prefix. But some views can show all cluster information using only
local node data, without distributed requests (for example
IGNITE_NODE_METRICS, IGNITE_PART_ASSIGNMENT, IGNITE_PART_ALLOCATION,
IGNITE_NODES, etc). Are they local or cluster views in this concept? Which
prefix should be used? And what about caches? Are they local or cluster? On
local node we can see cluster wide caches (replicated and distributed) and
caches for current node only. Local caches list may differ from node to
node. Which prefix should be used for this view? And one more, there is no
sense for some views to make them cluster wide (for example
INGNITE_INSTANCE). Should we name it LOCAL_INSTANCE without creating
INSTANCE view?
So, next steps: split PR, change schema name (IGNITE?), change view name
for caches (CACHES, LOCAL_CACHES?)
2018-01-24 13:03 GMT+03:00 Vladimir Ozerov <voze...@gridgain.com>:
> Hi Alex,
>
> System views could be extremely valuable addition for Ignite. Ideally, user
> should be able to monitor and manage state of the whole cluster with a
> single SQL command line. We have plans to implement it for a very long
> time. However, this is very sensitive task which should take a lot of
> moving pieces in count, such as usability, consistency, performance,
> security, etc..
>
> Let me point several major concerns I see at the moment:
>
> 1) Usability: INFORMATION_SCHEMA
> This schema is part of SQL ANSI standard. When creating system views, some
> vendors prefer to store them in completely different predefined schema
> (Oracle, MS SQL). Others prefer to keep them in INFORMATION_SCHEMA
> directly. Both approaches could work. However, the latter breaks separation
> of concerns - we store typical metadata near to possibly sensitive system
> data. Also it makes security management more complex - system data is very
> sensitive, and now we cannot simply grant access INFORMATIONAL_SCHEMA to
> user. Instead, we have to grant that access on per-view basis. For this
> reason my preference is to store system tables in separate schema, not in
> INFORMATION_SCHEMA
>
> 2) Consistency: local data
> One of implemented view GridH2SysViewImplInstance. Normally SQL users
> communicate with Ignite through JDBC/ODBC drivers. These drivers are
> connected to a single node, typically client node. Moreover, we will
> introduce high-availability feature when drivers were able to connect to
> any address from a predefined list. It renders this view useless, as you do
> not know which node you connected to. Also, local-only data cannot be
> joined in general case - you will receive different results on different
> nodes. The same goes for transactions, JVM info, etc.
>
> 3) Performance
> Suppose we fixed consistency of transactions and now this view shows
> transactions in the whole cluster with possibility to filter them by nodes
> - this is what user would expect out of the box. Another problem appears
> then - performance. How would we collect necessary data? How would we
> handle joins, when particular view could be scanned multiple times during
> query execution? How we achieve sensible consistency? Most probably we
> would collect remote data once when query is started, cache it somehow on
> query session level, and then re-use during joins. But again, this should
> be discussed separately.
>
> 4) Security: JVM info
> We should define clear boundaries of what info is exposed. JVM data along
> with running threads is critically sensitive information. We should not
> expose it until we have authorization capabilities.
>
> In order to start moving this code from prototype to production state we
> should start with the most simple and consistent views. E.g. IGNITE_CACHES.
> Let's move it to a separate PR, review infrastructure code, review view
> implementation, agree on proper naming and placement, and merge it. Then
> each and every view (or group of related views) should be discussed and
> reviewed separately.
>
> As far as node-local stuff, may be we should move it to a separate schema,
> or mark with special prefix. E.g. "IGNITE.TRANSACTIONS" - all transactions
> in the cluster, "IGNITE.LOCAL_TRANSACTIONS" - transactions on the local
> node. In this case we will be able to merge "local" stuff shortly, and
> implement more complex but at the same time much more useful distributed
> stuff later on.
>
> Makes sense?
>
> Vladimir.
>
>
> On Tue, Jan 23, 2018 at 8:30 PM, Alex Plehanov <plehanov.a...@gmail.com>
> wrote:
>
> > Hello, Igniters!
> >
> > For Ignite diagnostic usually it’s helpful to get some Ignite internals
> > information. But currently, in my opinion, there are no convenient tools
> > for this purpose:
> >
> > · Some issues can be solved by analyzing log files. Log files are
> > useful for dumps, but sometimes they are difficult to read. Also
> > interesting metrics can’t be received runtime by request, we need to wait
> > until Ignite will write these metrics by timeout or other events.
> >
> > · JMX is useful for scalar metrics. Complex and table data can
> also
> > be received, but it’s difficult to read, filter and sort them without
> > processing by specialized external tools. For most frequently used cases
> > almost duplicating metrics are created to show data in an easy-to-read
> > form.
> >
> > · Web-console is able to show table and complex data. Perhaps,
> > someday web-console will contain all necessary dashboards for most
> problem
> > investigation, but some non-trivial queries will not be covered anyway.
> > Also web-console needs additional infrastructure to work.
> >
> > · External “home-made” tools can be used for non-trivial cases.
> They
> > cover highly specialized cases and usually can’t be used as general
> purpose
> > tools.
> >
> > Sometimes we are forced to use more than one tool and join data by hands
> > (for example, current thread dump and data from logs).
> >
> > Often RDBMS for diagnostic purposes provides system views (for example,
> > DBA_% and V$% in Oracle), which can be queried by SQL. This solution
> makes
> > all internal diagnostic information available in a readable form (with
> all
> > possible filters and projections) without using any other internal or
> > external tools. My proposal is to create similar system views in Ignite.
> >
> > I implement working prototype (PR: [1]). It contains views:
> >
> > IGNITE_SYSTEM_VIEWS
> >
> > Registered system views
> >
> > IGNITE_INSTANCE
> >
> > Ignite instance
> >
> > IGNITE_JVM_THREADS
> >
> > JVM threads
> >
> > IGNITE_JVM_RUNTIME
> >
> > JVM runtime
> >
> > IGNITE_JVM_OS
> >
> > JVM operating system
> >
> > IGNITE_CACHES
> >
> > Ignite caches
> >
> > IGNITE_CACHE_CLUSTER_METRICS
> >
> > Ignite cache cluster metrics
> >
> > IGNITE_CACHE_NODE_METRICS
> >
> > Ignite cache node metrics
> >
> > IGNITE_CACHE_GROUPS
> >
> > Cache groups
> >
> > IGNITE_NODES
> >
> > Nodes in topology
> >
> > IGNITE_NODE_HOSTS
> >
> > Node hosts
> >
> > IGNITE_NODE_ADDRESSES
> >
> > Node addresses
> >
> > IGNITE_NODE_ATTRIBUTES
> >
> > Node attributes
> >
> > IGNITE_NODE_METRICS
> >
> > Node metrics
> >
> > IGNITE_TRANSACTIONS
> >
> > Active transactions
> >
> > IGNITE_TRANSACTION_ENTRIES
> >
> > Cache entries used by transaction
> >
> > IGNITE_TASKS
> >
> > Active tasks
> >
> > IGNITE_PART_ASSIGNMENT
> >
> > Partition assignment map
> >
> > IGNITE_PART_ALLOCATION
> >
> > Partition allocation map
> >
> >
> >
> > There are much more useful views can be implemented (executors
> diagnostic,
> > SPIs diagnostic, etc).
> >
> > Some usage examples:
> >
> > Cache groups and their partitions, which used by transaction more than 5
> > minutes long:
> >
> > SELECT cg.CACHE_OR_GROUP_NAME, te.KEY_PARTITION, count(*) AS ENTITIES_CNT
> > FROM INFORMATION_SCHEMA.IGNITE_TRANSACTIONS t
> > JOIN INFORMATION_SCHEMA.IGNITE_TRANSACTION_ENTRIES te ON t.XID = te.XID
> > JOIN INFORMATION_SCHEMA.IGNITE_CACHES c ON te.CACHE_NAME = c.NAME
> > JOIN INFORMATION_SCHEMA.IGNITE_CACHE_GROUPS cg ON c.GROUP_ID = cg.ID
> > WHERE t.START_TIME < TIMESTAMPADD('MINUTE', -5, NOW())
> > GROUP BY cg.CACHE_OR_GROUP_NAME, te.KEY_PARTITION
> >
> >
> >
> > Average CPU load on server nodes grouped by operating system:
> >
> > SELECT na.VALUE, COUNT(n.ID), AVG(nm.AVG_CPU_LOAD) AVG_CPU_LOAD
> > FROM INFORMATION_SCHEMA.IGNITE_NODES n
> > JOIN INFORMATION_SCHEMA.IGNITE_NODE_ATTRIBUTES na ON na.NODE_ID = n.ID
> AND
> > na.NAME = 'os.name'
> > JOIN INFORMATION_SCHEMA.IGNITE_NODE_METRICS nm ON nm.NODE_ID = n.ID
> > WHERE n.IS_CLIENT = false
> > GROUP BY na.VALUE
> >
> >
> >
> > Top 5 nodes by puts to cache ‘cache’:
> >
> > SELECT cm.NODE_ID, cm.CACHE_PUTS FROM
> > INFORMATION_SCHEMA.IGNITE_CACHE_NODE_METRICS cm
> > WHERE cm.CACHE_NAME = 'cache'
> > ORDER BY cm.CACHE_PUTS DESC
> > LIMIT 5
> >
> >
> >
> > Does this implementation interesting to someone else? Maybe any views are
> > redundant? Which additional first-priority views must be implemented? Any
> > other thoughts or proposal?
> >
> > [1] https://github.com/apache/ignite/pull/3413
> >
>
