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Session and User metrics are calculated through an estimation. Google Analytics provides a number of session metrics, including Session, Engaged sessions, and Engaged sessions per user. These metrics allow you to see data about the number of sessions that have started on your site or app.
As of October 2021, Google Analytics began updating the calculation method for session metrics in your standard and custom reports and in Explorations and Looker Studio to more efficiently count sessions with high accuracy and low error rate. As a result, you may notice a small difference in session counts from the previous calculation method.
In addition to being able to view session counts in Google Analytics, you can export your data to BigQuery so you can query your session counts through a SQL-like syntax. BigQuery has enough time and resources to calculate the precise number of sessions and therefore doesn't apply the efficient calculation method (called the HyperLogLog++ algorithm) for session metrics. Learn more
The cache backend (cache) stores session data only in your cache. This isfaster because it avoids database persistence, but you will have to considerwhat happens when cache data is evicted. Eviction can occur if the cache fillsup or the cache server is restarted, and it will mean session data is lost,including logging out users. To use this backend, set SESSION_ENGINEto "django.contrib.sessions.backends.cache".
Note that the JSONSerializercannot handle arbitrary Python data types. As is often the case, there is atrade-off between convenience and security. If you wish to store more advanceddata types including datetime and Decimal in JSON backed sessions, youwill need to write a custom serializer (or convert such values to a JSONserializable object before storing them in request.session). Whileserializing these values is often straightforward(DjangoJSONEncoder may be helpful),writing a decoder that can reliably get back the same thing that you put in ismore fragile. For example, you run the risk of returning a datetime thatwas actually a string that just happened to be in the same format chosen fordatetimes).
The examples in this section import the SessionStore object directlyfrom the django.contrib.sessions.backends.db backend. In your own code,you should consider importing SessionStore from the session enginedesignated by SESSION_ENGINE, as below:
When working with sessions internally, Django uses a session store object fromthe corresponding session engine. By convention, the session store object classis named SessionStore and is located in the module designated bySESSION_ENGINE.
The example below shows a custom database-backed session engine that includesan additional database column to store an account ID (thus providing an optionto query the database for all active sessions for an account):
USCIS regularly holds information sessions for the public. These sessions will help lawful permanent residents and others interested in naturalization learn about the naturalization process, eligibility requirements, testing, and citizenship rights and responsibilities. See the table below for upcoming events in your area. Some of these sessions may be available in foreign languages. Each session is free of charge and open to the public.
Register for upcoming sessions, once registered your place at the session is held for you. You may drop your registration at any time, you will also be given the option to add the event to your calendar and be reminded the day before the event.
The message received through the web portal reads 'You are not permitted to start any more sessions for this resource"
I have just disabled session reliability to see if that makes any difference though would be disappointed if the benefits of session reliability are negated by having to have it turned off for an issue that occurs once in a blue moon.
The listening sessions provided an opportunity for patient-focused input relevant to the selected drugs, including information related to clinical benefit of the selected drugs as compared to therapeutic alternatives, how the selected drugs address unmet need, and how the selected drugs impact specific populations. The sessions were listen-only; CMS did not respond to feedback during the sessions.
In spring 2023, the Copyright Office hosted four virtual listening sessions on the use of artificial intelligence to generate works in creative fields. Copyright Office staff asked participants to discuss their hopes, concerns, and questions about generative AI and copyright law. The sessions were fully remote and focused on literary works, including print journalism and software; visual arts; audiovisual works; and music and sound recordings.
The Office invites artists, members of creative industries, AI developers and researchers working in those media, and lawyers involved with these issues to participate as speakers using the speaker registration form. Please note that the Office will review all requests and will endeavor to invite participants representing diverse viewpoints on the subject matter discussed at each listening session. The Office may not be able to accommodate all requests. If we are unable to seat you as a speaker at these listening sessions, please note that there will be other opportunities to share your views on AI policy with the Office. Nonspeaking attendance will be open to the public, and recordings of the event will be posted on the Office website.
Creating a session is expensive. To avoid the performance cost each time adatabase operation is made, clients should keep a session pool, which is a poolof available sessions that are ready to use. The pool should store existing sessionsand return the appropriate type of session when requested, as well as handle cleanupof unused sessions. For an example of how to implement a session pool, see thesource code for one of the Spanner client libraries, such as theGo client library or the Java client library.
The client libraries have a default number of sessions in the session pool anda default number of gRPC channels in the channel pool. Both defaults are adequatefor most cases. The following are the default minimum and maximum sessions andthe default number of gRPC channels for each programming language.
The Node.js client does not support multiple gRPC channels. It is thereforerecommended to create multiple clients instead of increasing the size of thesession pool beyond 100 sessions for a single client.
The Ruby client does not support multiple gRPC channels. It is thereforerecommended to create multiple clients instead of increasing the size of thesession pool beyond 100 sessions for a single client.
The number of sessions that your application uses is equal to the number ofconcurrent transactions that your application executes. You should modify thedefault session pool settings only if you expect a single application instanceto execute more concurrent transactions than the default session pool can handle.
Increasing the number of active sessions uses additional resources on theSpanner database service and in the client library. Increasing thenumber of sessions beyond the actual need of the application could degrade theperformance of your system.
The session pool size for an application determines how many concurrenttransactions a single application instance can execute. Increasing the sessionpool size beyond the maximum concurrency that a single application instance canhandle is not recommended. If the application receives a burst of requeststhat goes beyond the number of sessions in the pool, the requests are queuedwhile waiting for a session to become available.
For some client libraries, Spanner reserves a portion of the sessionsfor read-write transactions, called the write-sessions fraction. If your appuses up all the read sessions, then Spanner uses the read-writesessions, even for read-only transactions. Read-write sessions requirespanner.databases.beginOrRollbackReadWriteTransaction. If the user is in thespanner.databaseReader IAM role, then the call failsand Spanner returns this error message:
To determine an optimal size of the session pool for a client process, set thelower bound to the number of expected concurrent transactions, and set the upperbound to an initial test number, such as 100. If the upper bound is not adequate,increase it. Increasing the number of active sessions uses additional resourceson the Spanner database service, so failing to clean up unused sessionscan degrade performance. For users working with the RPC API, we recommend havingno more than 100 sessions per gRPC channel.
One scenario for keeping sessions alive is to handle regular peak demand on thedatabase. If heavy database use occurs daily from 9:00 AM to 6:00 PM, youshould keep some idle sessions alive during that time, since they are likelyrequired for the peak usage. After 6:00 PM, you can let Spanner dropidle sessions. Prior to 9:00 AM each day, create some new sessions so they willbe ready for the expected demand.
If you are creating a client library, don't expose sessions to the clientlibrary consumer. Provide the ability for the client to make database callswithout the complexity of creating and maintaining sessions. For an example of aclient library that hides the session details from the client library consumer,see the Spanner client library for Java.
You can use the ListSessions command to monitor active sessions in your databasefrom the command line, with the REST API, or with the RPC API. ListSessionsshows the active sessions for a given database. This is useful if you need tofind the cause of a session leak. (A session leak is an incident where sessionsare being created but not returned to a session pool for reuse.)
ListSessions lets you view metadata about your active sessions, includingwhen a session was created and when a session was last used. Analyzing this datawill point you in the right direction when troubleshooting sessions. If mostactive sessions don't have a recent approximate_last_use_time, this couldindicate that sessions aren't being reused properly by your application. See theRPC API reference for more information about the approximate_last_use_time field.
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