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RFC - SIP: Session Initiation Protocol

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Often, a registrar server for a domain is co-located with the proxy for that domain. It is an important concept that the distinction between types of SIP servers is logical, not physical. Bob is not limited to registering from a single device.

For example, both his SIP phone at home and the one in the office could send registrations.

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This information is stored together in the location Rosenberg, et. Session Initiation Protocol June service and allows a proxy to perform various types of searches to locate Bob. Similarly, more than one user can be registered on a single device at the same time. The location service is just an abstract concept.

It generally contains information that allows a proxy to input a URI and receive a set of zero or more URIs that tell the proxy where to send the request.

Registrations are one way to create this information, but not the only way.

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Arbitrary mapping functions can be configured at the discretion of the administrator. Finally, it is important to note that in SIP, registration is used for routing incoming SIP requests and has no role in authorizing outgoing requests. The complete set of SIP message details for this registration example is in Section The protocol behavior is described as layers for the purpose of presentation, allowing the description of functions common across elements in a single section.

It does not dictate an implementation in any way. When we say that an element "contains" a layer, we mean it is compliant to the set of rules defined by that layer. Not every element specified by the protocol contains every layer. Furthermore, the elements specified by SIP are logical elements, not physical ones. A physical realization can choose to act as different logical elements, perhaps even on a transaction-by-transaction basis.

The lowest layer of SIP is its syntax and encoding. Session Initiation Protocol June The second layer is the transport layer. It defines how a client sends requests and receives responses and how a server receives requests and sends responses over the network. All SIP elements contain a transport layer.

The transport layer is described in Section The third layer is the transaction layer. Transactions are a fundamental component of SIP. A transaction is a request sent by a client transaction using the transport layer to a server transaction, along with all responses to that request sent from the server transaction back to the client. The transaction layer handles application-layer retransmissions, matching of responses to requests, and application-layer timeouts.

Any task that a user agent client UAC accomplishes takes place using a series of transactions. Discussion of transactions can be found in Section User agents contain a transaction layer, as do stateful proxies. Stateless proxies do not contain a transaction layer. The transaction layer has a client component referred to as a client transaction and a server component referred to as a server transactioneach of which are represented by a finite state machine that is constructed to process a particular request.

The layer above the transaction layer is called the transaction user TU. Each of the SIP entities, except the stateless proxy, is a transaction user.

When a TU wishes to send a request, it creates a client transaction instance and passes it the request along with the destination IP address, port, and transport to which to send the request.

A TU that creates a client transaction can also cancel it. When a client cancels a transaction, it requests that the server stop further processing, revert to the state that existed before the transaction was initiated, and generate a specific error response to that transaction. The SIP elements, that is, user agent clients and servers, stateless and stateful proxies and registrars, contain a core that distinguishes them from each other.

Cores, except for the stateless proxy, are transaction users. For a UAC, these rules govern the construction of a request; for a UAS, they govern the processing of a request and generating a response. Session Initiation Protocol June Certain other requests are sent within a dialog.

A dialog is a peer-to-peer SIP relationship between two user agents that persists for some time. The dialog facilitates sequencing of messages and proper routing of requests between the user agents. When a UAC sends a request that is within the context of a dialog, it follows the common UAC rules as discussed in Section 8 but also the rules for mid-dialog requests. Section 12 discusses dialogs and presents the procedures for their construction and maintenance, in addition to construction of requests within a dialog.

A session is a collection of participants, and streams of media between them, for the purposes of communication. Section 13 discusses how sessions are initiated, resulting in one or more SIP dialogs. Section 14 discusses how characteristics of that session are modified through the use of an INVITE request within a dialog. Finally, section 15 discusses how a session is terminated. The procedures of Sections 81011121314and 15 deal entirely with the UA core Section 9 describes cancellation, which applies to both UA core and proxy core.

Section 16 discusses the proxy element, which facilitates routing of messages between user agents. Typically, the location service is populated through registrations. An AOR is frequently thought of as the "public address" of the user. In order to determine how the request should be answered, it acts as a user agent client UAC and generates requests. Unlike a proxy server, it maintains dialog state and must participate in all requests sent on the dialogs it has established.

Session Initiation Protocol June Call: A call is an informal term that refers to some communication between peers, generally set up for the purposes of a multimedia conversation. Another name for a dialog [ 31 ]; no longer used in this specification. A call stateful proxy is always transaction stateful, but the converse is not necessarily true.

Clients may or may not interact directly with a human user. User agent clients and proxies are clients. A multimedia session see below that contains multiple participants. Core designates the functions specific to a particular type of SIP entity, i. All cores, except those for the stateless proxy, are transaction users. A dialog is identified by a call identifier, local tag, and a remote tag.

A dialog was formerly known as a call leg in RFC A direction of message forwarding within a transaction that refers to the direction that requests flow from the user agent client to user agent server. A response that terminates a SIP transaction, as opposed to a provisional response that does not.

All 2xx, 3xx, 4xx, 5xx and 6xx responses are final. A header is a component of a SIP message that conveys information about the message.

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It is structured as a sequence of header fields. A header field is a component of the SIP message header. A header field can appear as one or more header field rows.

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Header field rows consist of a header field name and zero or more header field values. Multiple header field values on a Rosenberg, et. Session Initiation Protocol June given header field row are separated by commas.

Some header fields can only have a single header field value, and as a result, always appear as a single header field row. A header field value is a single value; a header field consists of zero or more header field values.

The domain providing service to a SIP user. Typically, this is the domain present in the URI in the address-of-record of a registration. Same as a provisional response.

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Initiator, Calling Party, Caller: A caller retains this role from the time it sends the initial INVITE that established a dialog until the termination of that dialog. A location service is used by a SIP redirect or proxy server to obtain information about a callee's possible location s. It contains a list of bindings of address-of- record keys to zero or more contact addresses.

A request that arrives at a proxy, is forwarded, and later arrives back at the same proxy. When it arrives the second time, its Request-URI is identical to the first time, and other header fields that affect proxy operation are unchanged, so that the proxy would make the same processing decision on the request it made the first time.

Looped requests are errors, and the procedures for detecting them and handling them are described by the protocol. A proxy is said to be loose routing if it follows the procedures defined in this specification for processing of the Route header field. These procedures separate the destination of the request present in the Request-URI from Rosenberg, et.

Session Initiation Protocol June the set of proxies that need to be visited along the way present in the Route header field. A proxy compliant to these mechanisms is also known as a loose router. Data sent between SIP elements as part of the protocol. SIP messages are either requests or responses. The method is the primary function that a request is meant to invoke on a server.

The method is carried in the request message itself. A proxy that receives requests from a client, even though it may not be the server resolved by the Request-URI. Typically, a UA is manually configured with an outbound proxy, or can learn about one through auto-configuration protocols. In a parallel search, a proxy issues several requests to possible user locations upon receiving an incoming request. Rather than issuing one request and then waiting for the final response before issuing the next request as in a sequential search, a parallel search issues requests without waiting for the result of previous requests.

A response used by the server to indicate progress, but that does not terminate a SIP transaction. An intermediary entity that acts as both a server and a client for the purpose of making requests on behalf of other clients. A proxy server primarily plays the role of routing, which means its job is to ensure that a request is sent to another entity "closer" to the targeted user.

Proxies are also useful for enforcing policy for example, making sure a user is allowed to make a call. A proxy interprets, and, if necessary, rewrites specific parts of a request message before forwarding it. A client recurses on a 3xx response when it generates a new request to one or more of the URIs in the Contact header field in the response.

A redirect server is a user agent server that generates 3xx responses to requests it receives, directing the client to contact an alternate set of URIs. Session Initiation Protocol June Registrar: A registrar is a server that accepts REGISTER requests and places the information it receives in those requests into the location service for the domain it handles. A SIP message sent from a client to a server, for the purpose of invoking a particular operation. A SIP message sent from a server to a client, for indicating the status of a request sent from the client to the server.

Ringback is the signaling tone produced by the calling party's application indicating that a called party is being alerted ringing. A route set can be learned, through headers like Record-Route, or it can be configured.

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A server is a network element that receives requests in order to service them and sends back responses to those requests. Examples of servers are proxies, user agent servers, redirect servers, and registrars. In a sequential search, a proxy server attempts each contact address in sequence, proceeding to the next one only after the previous has generated a final response.

A 2xx or 6xx class final response always terminates a sequential search. From the SDP specification: A multimedia conference is an example of a multimedia session. As defined, a callee can be invited several times, by different calls, to the same session. If SDP is used, a session is defined by the concatenation of the SDP user name, session id, network type, address type, and address elements in the origin field.

A SIP transaction occurs between a client and a server and comprises all messages from the first request sent from the client to the server up to a final non-1xx response Rosenberg, et.

Session Initiation Protocol June sent from the server to the client. A spiral is a SIP request that is routed to a proxy, forwarded onwards, and arrives once again at that proxy, but this time differs in a way that will result in a different processing decision than the original request. Typically, this means that the request's Request-URI differs from its previous arrival. For example, with the three tables below, it would not be possible to build a visual showing each Customer[Gender], and the number of Product[Category] bought by each.

Use of such bi-directional filtering is described in this detailed whitepaper the paper presents examples in the context of SQL Server Analysis Services, but the fundamental points apply equally to Power BI. Again, the limitation is imposed due to the performance implications. One particularly important application of this is when defining Row Level Security as part of the report, as a common pattern is to have a many-many relationship between the users and the entities they are allowed access to, and use of bi-directional filtering is necessary to enforce this.

However, use of bi-directional filtering for DirectQuery models should be used judiciously, with careful attention paid to any detrimental impact on performance.

When using DirectQuery, it is not possible to use the Clustering capability, to automatically find groups Reporting limitations Almost all reporting capabilities are supported for DirectQuery models.

As such, so long as the underlying source offers a suitable level of performance, the same set of visualizations can be used. However, there are some important limitations in some of the other capabilities offered in the Power BI service after a report is published, as described in the following bullets: Quick Insights is not supported: Power BI Quick Insights searches different subsets of your dataset while applying a set of sophisticated algorithms to discover potentially-interesting insights.

Given the need for very high performance queries, this capability is not available on datasets using DirectQuery. However, it is currently not supported on datasets using DirectQuery.

Using Explore in Excel will likely result in poorer performance: While this capability is supported on datasets using DirectQuery, the performance is generally slower than creating visuals in Power BI, and therefore if the use of Excel is important for your scenarios, this should be accounted for in your decision to use DirectQuery.

Security As discussed earlier in this article, a report using DirectQuery will always use the same fixed credentials to connect to the underlying data source, after publish to the Power BI service. Hence immediately after publish of a DirectQuery report, it is necessary to configure the credentials of the user that will be used.

Until this is done, opening the report on the Power BI service would result in an error. Once the user credentials are provided, then those credentials will be used, irrespective of the user who opens the report. In this regard it is exactly like imported data, in that every user will see the same data, unless Row Level Security has been defined as part of the report. Hence the same attention must be paid to sharing the report, if there are any security rules defined in the underlying source.

Behavior in the Power BI service This section describes the behavior of a DirectQuery report in the Power BI service, primarily so as to be able to understand the degree of load that will be placed on the back end data source, given the number of users that the report and dashboard will be shared with, the complexity of the report, and whether Row Level Security has been defined in the report.

Reports — opening, interacting with, editing When a report is opened, then all the visuals on the currently visible page will refresh. Each visual will generally require at least one query to the underlying data source. Some visuals might require more than one query for example, if it showed aggregate values from two different fact tables, or contained a more complex measure, or contained totals of a non-additive measure like Count Distinct.

Moving to a new page will result in those visuals being refreshed, resulting in a new set of queries to the underlying source. Every user interaction on the report might result in visuals being refreshed. For example, selecting a different value on a slicer will require sending a new set of queries to refresh all of the effected visuals.

The same is true for clicking on a visual to cross-highlight other visuals, or changing a filter. Similarly of course, editing a new report will require queries to be sent for each step on the path to produce the final desired visual.

There is some caching of results, so that the refresh of a visual will be instantaneous if the exact same results have recently been obtained.

Such caches are not shared across users, if there is any Row Level Security defined as part of the report. Dashboard Refresh Individual visuals, or entire pages, can be pinned to dashboard as tiles. Tiles based on DirectQuery datasets are then refreshed automatically according to a schedule, resulting in queries being sent to the backend data source. By default, this occurs every hour, but can be configured as part of Dataset settings to be between weekly, and every 15 minutes.

If no Row Level Security is defined in the model, this means that each tile would be refreshed once, and the results shared across all users. If Row Level Security is defined, then there can be a large multiplier effect — each tile requires separate queries per user to be sent to the underlying source.

Hence a dashboard with ten tiles, shared with users, created on a dataset using DirectQuery with Row Level Security, and configured to refresh every 15 minutes, would result in at least queries being sent every 15 minutes to the back end source.

Hence careful consideration must be paid to the use of Row Level Security, and the configuring of the refresh schedule.

Timeouts A timeout of four minutes is applied to individual queries in the Power BI service, and queries taking longer than that will simply fail.

As stressed earlier, it is recommended that DirectQuery be used for sources that provide near interactive query performance, so this limit is intended to prevent issues from overly long execution times. Other implications Some other general implications of using DirectQuery are the following: If data is changing, it is necessary to Refresh to ensure the latest data is shown: Given the use of caches, there is no guarantee that the visual is always showing the latest data.

For example, a visual might show the transactions in the last day. Then due to a slicer being changed, it might refresh to show the transactions for the last two days, including some very recent, newly arrived transactions.

Returning the slicer to its original value would result in it again showing the cached value previously obtained, that would not include the newly arrived transaction seen before. Selecting Refresh will clear any caches, and refresh all the visuals on the page to show the latest data. If data is changing, there is no guarantee of consistency between visuals: Different visuals, whether on the same page or on different pages, might be refreshed at different times.

Thus if the data in the underlying source is changing, there is no guarantee that each visual will be showing the data at the exact same point of time. Indeed, given that sometimes more than one query is required for a single visual for example, to obtain the details and the totals then consistency even within a single visual is not guaranteed. To guarantee this would require the overhead of refreshing all visuals whenever any visual refreshed, in tandem with the use of costly features like Snapshot Isolation in the underlying data source.

This issue can be mitigated to a large extent by again selecting Refresh, to refresh all of the visuals on the page. And it should be noted that even if using Import mode, there is a similar problem of guaranteeing consistency if importing data from more than one table. Refresh in Power BI Desktop is needed to reflect any metadata changes: After a report is published, Refresh will simply refresh the visuals in the report. If the schema of the underlying source has changed, then those changes are not automatically applied to change the available fields in the field list.

Thus if tables or columns have been removed from the underlying source, it might result in query failure upon refresh. Opening the report in Power BI Desktop, and choosing Refresh, will update the fields in the model to reflect the changes.

Limit of one million rows returned on any query: There is a fixed limit of one million rows placed on the number of rows that can be returned in any single query to the underlying source. However, the limit can occur in cases where Power BI is not fully optimizing the queries sent, and there is some intermediate result being requested that exceeds the limit. It can also occur whilst building a visual, on the path to a more reasonable final state. For example, including Customer and TotalSalesQuantity would hit this limit if there were more than 1m customers, until some filter were applied.

Note that while it's generally possible to switch a model from DirectQuery mode to use import mode, this means all the necessary data must be imported. It is also not possible to switch back primarily due to the set of features not supported in DirectQuery mode. DirectQuery models over multidimensional sources like SAP BW, also cannot be switched from DirectQuery to import, due to the completely different treatment of external measures. Some sources are also available directly from within the Power BI service.

For example, it is possible for a business user to use Power BI to connect to their data in Salesforce, and immediately get a dashboard, without use of Power BI Desktop. Only two of the DirectQuery enabled-sources are available directly in the service: The reason is that when the connection is initially made in the Power BI service, many key limitations will apply, meaning that while the start point was easy starting in the Power BI servicethere are limitations on enhancing the resulting report any further for example, it's not possible then to create any calculations, or use many analytical features, or even refresh the metadata to reflect any changes to the underlying schema.

Guidance for using DirectQuery successfully If you're going to use DirectQuery, then this section provides you with some high level guidance on how to ensure success. The guidance in this section is derived from the implications of using DirectQuery that have been described in this article.

Backend data source performance It is strongly recommended to validate that simple visuals will be able to refresh in a reasonable time. This should be within 5 seconds to have a reasonable interactive experience.

Certainly if visuals are taking longer than 30 seconds, then it's highly likely that further issues will occur following publication of the report, which will make the solution unworkable. If queries are slow, then the first point of investigation is to examine the queries being sent to the underlying source, and the reason for the query performance being observed.

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This topic doesn't cover the wide range of database optimization best practices across the full set of potential underlying sources, but it does apply to the standard database practices that apply to most situations: Relationships based on integer columns generally perform better than joins on columns of other data types The appropriate indexes should be created, which generally means the use of column store indexes in those sources that support them for example, SQL Server.

Any necessary statistics in the source should be updated Model Design Guidance When defining the model, consider doing the following: Avoid complex queries in Query Editor. The query that's defined in the Query Editor will be translated into a single SQL query, that will then be included in the subselect of every query sent to that table.

If that query is complex, it might result in performance issues on every query sent. The actual SQL query for a set of steps can be obtained by selecting the last step in Query Editor, and choosing View Native Query from the context menu. At least initially, it is recommended to limit measures to simple aggregates.

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Then if those perform in a satisfactory manner, more complex measures can be defined, but paying attention to the performance for each.

Avoid relationships on calculated columns. This is particularly relevant to databases where it is necessary to perform multi-column joins. The common workaround is to concatenate the columns together using a calculated column, and base the join on that. While this workaround is reasonable for imported data, in the case of DirectQuery it results in a join on an expression, that commonly prevents use of any indexes, and leads to poor performance.

The only workaround is to actually materialize the multiple columns into a single column in the underlying database. Avoid relationships on uniqueidentifier columns. Power BI does not natively support a datatype of uniqueidentifier. Hence defining a relationship between columns of type uniqueidentifier column will result in a query with a join involving a Cast.

Again, this commonly leads to poor performance. Until this case is specifically optimized, the only workaround is to materialize columns of an alternative type in the underlying database. Hide the to column on relationships.

The to column on relationships commonly the primary key on the to table should be hidden, so that it does not appear in the field list, and therefore cannot be used in visuals.

Often the columns on which relationships are based are in fact system columns for example, surrogate keys in a data warehouse and hiding such columns is good practice anyway. If the column does have meaning, then introduce a calculated column that is visible, and that has a simple expression of being equal to the primary key.

The reason for doing this is simply to avoid a performance issue that can occur otherwise if a visual includes the primary key column. Examine all uses of calculated columns and data type changes. Use of these capabilities are not necessarily harmful, they result in the queries sent to the underlying source containing expressions rather than simple references to columns, that again might result in indexes not being used. Avoid use of the preview bi-directional cross filtering on relationships.

Experiment with setting Assume referential integrity. This generally improves query performance, though it does depend on the specifics of the data source. Do not use the relative data filtering in Query Editor. It's possible to define relative date filtering in Query Editor. For example, to filter to the rows where the date is in the last 14 days. However, this will be translated into a filter based on the fixed date, as at the time the query was authored. This can be seen from viewing the native query.

This is almost certainly not what was wanted. To ensure the filter is applied based upon the date as at the time the report is executed then instead apply the filter in the report as a Report Filter. Currently this would be done by creating a calculated column calculating the number of days ago using the DAX DATE functionand then using that calculated column in a filter.

Report Design Guidance When creating a report using a DirectQuery connection, adhere to the following guidance: Consider use of Query Reduction options: Power BI provides options in the report to send fewer queries, and to disable certain interactions that would result in a poor experience if the resulting queries take a long time to execute.

Checking box selections on the Query reduction let you disable cross-highlighting throughout your entire report. Your selections can then be used to filter the data.

These options will apply to your report while you interact with it in Power BI Desktop, as well as when your users consume the report in the Power BI service.

Always apply any applicable filters at the start of building a visual. For example, rather than drag in the TotalSalesAmount, and ProductName, then filter to a particular year, apply the filter on Year at the very start. This is because each step of building a visual will send a query, and whilst it is possible to then make another change before the first query has completed, this still leaves unnecessary load on the underlying source.

By applying filters early, it generally makes those intermediate queries less costly. Also, failing to apply filters early can result in hitting the 1m row limit above. Limit the number of visuals on a page: When a page is opened or some page level slicer or filter changed then all of the visuals on a page are refreshed. There is also a limit on the number of queries that are sent in parallel, hence as the number of visuals increases, some of the visuals will be refreshed in a serial manner, increasing the time taken to refresh the entire page.

Using DirectQuery in Power BI

For this reason it's recommended to limit the number of visuals on a single page, and instead have more, simpler pages. Consider switching off interaction between visuals: By default, visualizations on a report page can be used to cross-filter and cross-highlight the other visualizations on the page.

In DirectQuery such cross-filtering and cross-highlighting require queries to be submitted to the underlying source, so the interaction should be switched off if the time taken to respond to users' selections would be unreasonably long.

However, this interaction can be switched off, either for the entire report as described above for Query reduction optionsor on a case-by-case basis as described in this article. In addition to the above list of suggestions, note that each of the following reporting capabilities can cause performance issues: Visuals containing measures or aggregates of columns can contain filters in those measures. For example, the visual below shows SalesAmount by Category, but only including those Categories with more than 20M of sales.

This will result in two queries being sent to the underlying source: This generally performs just fine if there are hundreds or thousands of categories, as in this example.

Performance can degrade if the number of categories is much larger and indeed, the query will fail if there were more than a million categories meeting the condition, due to the one million row limit discussed earlier. Advanced filters can be defined to filter on only the Top or Bottom N values ranked by some measure, for example, to only include the Top 10 Categories in the visual above.

This will again result in two queries being sent to the underlying source. However, the first query will return all categories from the underlying source, and then the TopN are determined based on the returned results. Depending on the cardinality of the column involved, this can lead to performance issues or query failures due to the 1m row limit. Generally, any aggregation Sum, Count Distinct, so on is pushed to the underlying source. However, this is not true for Median, as this aggregate is generally not supported by the underlying source.

In such cases, the detail data is retrieved from the underlying source, and the Median calculated from the returned results. This is reasonable when the median is to be calculated over a relatively small number of results, but performance issues or query failures due to the 1m row limit will occur if the cardinality is large. These filters can certainly result in degraded performance for some data sources.