Comparing The Performance Of Reading Data From Files With File.Contents And Web.Contents In Power Query And Power BI

In my last post I mentioned the Power Query engine’s persistent cache, which in some scenarios caches the data read from a data source when a query is refreshed. Another important nugget of information that Ehren von Lehe of the Power Query dev team mentioned in a post on the Power Query MSDN forum recently is the fact that if you use File.Contents to get data from a file then the persistent cache is not used, but if you use Web.Contents to get data from the same file then the persistent cache is used. I guess the thinking here is that there is no point creating an on-disk cache containing the contents of a file that is already on disk.

Using Process Monitor (see here and here for more information on how to do this) to view how much data is read from disk when a query is run it is possible to see this in action. Here’s the graph showing how much data is read from a 150MB csv file when a slow query is refreshed. This particular slow query results in five reads to the csv file – it’s more or less the same scenario from my second Process Monitor blog post here, with the query itself described in a lot of detail here. Here’s a graph of the data captured by Process Monitor showing time in seconds on the X axis and amount of data read in MB on the Y axis:

image

Since this query uses File.Contents to get the data from the csv file, the persistent cache is not used; as you can see, the graph shows clearly that the full contents of the csv file are read five times.

The same query altered to use Web.Contents shows just two full reads:

image

I have no idea why the file is read twice rather than once, but it’s definitely different behaviour to the version that uses File.Contents.

As far as I can see it is possible to replace File.Contents with Web.Contents in every case. So, if you have the following expression:

File.Contents("c:\users\myuser\Desktop\file.txt")

You can just replace it with:

Web.Contents("c:\users\myuser\Desktop\file.txt")

Which one is faster though? Just because a query reads data from disk more often does not necessarily mean that it will be slower. In the above scenario, with the csv file stored on my local hard drive, the Web.Contents version of the query refreshes in 18 seconds while the File.Contents version refreshes in 14 seconds. Replacing the csv file with an Excel file that contains the same data (remember that Excel files are a lot slower than csv files to read data from, as I showed here) results in the version of the query that uses File.Contents running in 205 seconds, while the version that uses Web.Contents running in 297 seconds. So it looks like, in most cases, File.Contents is the right choice when reading data from a file (as you would hope).

However, when using the same csv file stored on a network file share, the Web.Contents version takes 23 seconds while the File.Contents version takes 25 seconds. So maybe if you are dealing with files that are stored remotely over a slow connection it might be worth replacing File.Contents with Web.Contents to see if you get any performance benefits. There may be other situations where Web.Contents is the faster choice too. If you test this and see a difference, let me know by leaving a comment!

UPDATE: please also read Curt Hagenlocher’s comment below – Web.Contents may be changed in the future so it only works with http/https

The CredentialQuery Option For Web.Contents() In Power BI Custom Data Connectors

There’s a new, as yet undocumented, option for the Web.Contents() M function that is only available for custom data connectors and not in Power BI Desktop: CredentialQueryOption. It does the same thing as the Query option, but it stops the values you are passing to the query parameter from being logged in Power BI’s diagnostic logs, so it’s useful if you are passing sensitive information such as passwords.

For example, consider the following call to Web.Contents() used in a custom data connector:

Web.Contents(
 "https://data.gov.uk/api", 
 [RelativePath="3/action/package_search", 
 Query=[q="cows"]
]
)

When the custom data connector is used in Power BI Desktop, if diagnostic logging is turned on in the Options dialog:

image

…then, if you look in the log files you’ll see the entire url called including the search term “cows”:

image

However, if you change the M code to:

Web.Contents(
 "https://data.gov.uk/api", 
 [RelativePath="3/action/package_search", 
 CredentialQuery=[q="cows"]
]
)

So that the CredentialQuery option is used instead of the Query option, the search term will not appear in the log file.

Thanks to Curt Hagenlocher for providing this information.

Web.Contents(), Caching And The ExcludedFromCacheKey Option In Power BI And Power Query

When you’re using the Web.Contents() M function to call a web service from Power Query or Power BI, you don’t necessarily get one HTTP request each time you call the function: some caching takes place, so that if you make the same request multiple times your query won’t waste time asking for the same data over and over. In this post I’m going to share the results of some tests I made to show how caching works with Web.Contents() and what factors influence it.

For my tests I built a simple web service in Microsoft Flow, similar to the one I blogged about here, that accepts a HTTP POST request and calls a stored procedure in an Azure SQL Database. The stored procedure then updates a table in the database and this in turn allows me to count the number of times the web service is called. Finally, the web service returns the value 0 if the stored procedure has executed successfully.

This web service can then be called from either Power Query or Power BI using the Web.Contents() function, something like this (because the URL for the web service is very long I stored it in a parameter called WebServiceURL):

let
    Source = Web.Contents(
	WebServiceURL,
	[Content=Text.ToBinary("Hello")]
	),
    #"Imported JSON" = Json.Document(Source,1252)
in
    #"Imported JSON"

The output of the query when run in Power Query and loaded to an Excel table is this:

image

The first important thing to point out is that the above query, when refreshed in the latest versions of Power Query (I’m running Excel 2016 build 7571.2109) and Power BI (build 2.41.4581.361- November 2016 release), results in a single call to the web service. It might seem like I’m stating the obvious but in the past I’ve seen plenty of cases where a data source has been queried multiple times by Power Query/Power BI even if I was only expecting it to be queried once.

Now, let’s look at a query that calls this web service several times. Here’s the query above converted to a function called fnCallWebService:

() => 
let
    Source = Web.Contents(
	WebServiceURL,
	[Content=Text.ToBinary("Hello")]),
    #"Imported JSON" = Json.Document(Source,1252)
in
    #"Imported JSON"

Here’s a query that calls this function once for each row of the following table:

image

let
    Source = Excel.CurrentWorkbook(){[Name="MyTable"]}[Content],
    #"Changed Type" = Table.TransformColumnTypes(
	Source,
	{{"Row", Int64.Type}}),
    #"Invoked Custom Function" = Table.AddColumn(
	#"Changed Type", 
	"fnCallWebService", 
	each fnCallWebService())
in
    #"Invoked Custom Function"

In the query above I used the Invoke Custom Function button to call the function for each row in the source table and put the value returned by the function in a new column. The output is this:

image

Even though the function is called four times, once for each row in the original table, that does not mean that the web service is called four times – it isn’t, it’s only called once. In this case Power BI/Power Query knows that each of the four calls to the function is making an identical request to the web service and so it only goes to the web service once, and thereafter uses a cached result the other three times.

One way to stop this caching from taking place is to add an HTTP header to the request to the web service and pass a different value to that header for each call. Here’s another version of my function, now called fnCallWebServiceWithHeaders, which this time takes a number as a parameter and then passes that number to the web service via a header called MyHeader:

(RowNum as number) => let
    Source = Web.Contents(
	WebServiceURL,
	[Content=Text.ToBinary("Hello"), 
	Headers=[MyHeader=Text.From(RowNum)]]),
    #"Imported JSON" = Json.Document(Source,1252)
in
    #"Imported JSON"

Now if I call this function for each row of the table, and for each call pass the value in the [Row] column through to the function like so:

image

let
    Source = Excel.CurrentWorkbook(){[Name="MyTable"]}[Content],
    #"Changed Type" = Table.TransformColumnTypes(
	Source,
	{{"Row", Int64.Type}}),
    #"Invoked Custom Function" = Table.AddColumn(
	#"Changed Type", 
	"fnCallWebServiceWithHeaders", 
	each fnCallWebServiceWithHeaders([Row]))
in
    #"Invoked Custom Function"

…the web service gets hit four times. The presence of a different value for the MyHeader header in each request is enough to prevent any caching from taking place.

It is possible, however, to get Power BI/Power Query to ignore one or more headers when working out whether caching should take place using the ExcludedFromCacheKey option in Web.Contents(). Here’s one more version of my function, now called fnCallWebServiceWithHeadersExlCache, which uses this option:

(RowNum as number) => 
let
    Source = Web.Contents(
	WebServiceURL,
	[Content=Text.ToBinary("Hello"), 
	Headers=[MyHeader=Text.From(RowNum)], 
	ExcludedFromCacheKey={"MyHeader"}]),
    #"Imported JSON" = Json.Document(Source,1252)
in
    #"Imported JSON"

The ExcludedFromCacheKey option takes a list of text values which represent the names of headers that are to be ignored when considering which requests can be cached. In the example above my list contains just the one header, MyHeader, and when this is used in a query like so:

let
    Source = Excel.CurrentWorkbook(){[Name="MyTable"]}[Content],
    #"Changed Type" = Table.TransformColumnTypes(
	Source,
	{{"Row", Int64.Type}}),
    #"Invoked Custom Function" = Table.AddColumn(
	#"Changed Type", 
	"fnCallWebServiceWithHeaders", 
	each fnCallWebServiceWithHeadersExlCache([Row]))
in
    #"Invoked Custom Function"

…even though the function is called four times, once for each row in the table, and even though each time Web.Contents() is called it is with a different value passed through to the MyHeader header, only one request is made to the web service and the three subsequent requests are answered from cache again.

In summary, if you’re calling a web service multiple times in a query and especially if you’re using the Headers option in Web.Contents(), this is important stuff to understand because caching can make a big difference to the performance of your queries.

Web.Contents(), M Functions And Dataset Refresh Errors In Power BI

One slightly frustrating feature of Power BI is that some of the cool stuff you can do in M code for loading data, and which works in Power BI Desktop (and in Power Query), causes errors when you try to refresh your dataset after it has been published to PowerBI.com. I recently learned some interesting tricks for working around these problems when you are using Web.Contents() and M custom functions, which I thought deserved a wider audience and which are the subject of this post; thanks are due to Curt Hagenlocher of Microsoft and Idan Cohen for sharing this information.

First of all, I recommend you read my previous post on using the RelativePath and Query options with Web.Contents() to get some background, not just on the M functionality I’ll be using but also on the web service I’ll be using in my examples.

Let’s look at an example of where the problem occurs. The following M query uses a function to call the UK government’s open data metadata search API multiple times and then return a result into a table:

let
    Terms = 
      #table(
       {"Term"},
       {{"apples"}, {"oranges"}, {"pears"}}
       ),
    SearchSuccessful = (Term) => 
    let
        Source = 
         Json.Document(
           Web.Contents(
             "https://data.gov.uk/api/3/action/package_search?q=" 
             & Term
            )
           ),
        Success = Source[success]
    in
        Success,
    Output = 
     Table.AddColumn(
       Terms, 
       "Search Successful", 
       each SearchSuccessful([Term])
      )
in
    Output

Here’s the output:

image

This is just a variation on the widely-used M pattern for using functions to iterate over and combine data from multiple data sources; Matt Masson has a good blog describing this pattern here. In this case I’m doing the following:

  • Defining a table using #table() with three rows containing three search terms.
  • Defining a function that calls the metadata API. It takes one parameter, a search term, and returns a value indicating whether the search was successful or not from the JSON document returned. What the API actually returns isn’t relevant here, though, just the fact that I’m calling it. Note the highlighted lines in the code above that show how I’m constructing the URL passed to Web.Contents() by simply concatenating the base URL with the string passed in via the custom function’s Term parameter.
  • Adding a custom column to the table returned by the first step, and calling the function defined in the second step using the search term given in each row.

This query refreshes with no problems in Power BI Desktop. However, when you publish a report that uses this code to PowerBI.com and try to refresh the dataset, you’ll see that refresh fails and returns a rather unhelpful error message:

Data source error Unable to refresh the model (id=1264553) because it references an unsupported data source.

image

image

The problem is that when a published dataset is refreshed, Power BI does some static analysis on the code to determine what the data sources for the dataset are and whether the supplied credentials are correct. Unfortunately in some cases, such as when the definition of a data source depends on the parameters from a custom M function, that static analysis fails and therefore the dataset does not refresh.

The good news is that when, as in this case, the data source is a call to Web.Contents() then Power BI only checks the base url passed into the first parameter during static analysis – and as my previous blog post shows, by using the RelativePath and Query options with Web.Contents() you can leave the value passed to the first parameter as a static string. Therefore, the following version of the query does refresh successfully in Power BI:

let
    Terms = 
      #table(
       {"Term"},
       {{"apples"}, {"oranges"}, {"pears"}}
       ),
    SearchSuccessful = (Term) => 
    let
        Source = 
         Json.Document(
           Web.Contents(
             "https://data.gov.uk/api/3/action/package_search", 
             [Query=[q=Term]]
            )
           ),
        Success = Source[success]
    in
        Success,
    Output = 
     Table.AddColumn(
       Terms, 
       "Search Successful", 
       each SearchSuccessful([Term])
      )
in
    Output

This technique will only work if the url passed to the first parameter of Web.Contents() is valid in itself, is accessible and does not return an error. But what if it isn’t? Luckily there’s another trick you can play: when you specify the Query option it can override parts of the url supplied in the first parameter. For example, take the following expression:

Web.Contents(
 "https://data.gov.uk/api/3/action/package_search?q=apples", 
 [Query=[q="oranges"]]
)

When static analysis is carried out before dataset refresh, the url

https://data.gov.uk/api/3/action/package_search?q=apples

..is evaluated. However when the dataset is actually refreshed, the search term in the Query option overrides the search term in the base url, so that the call to the web service that is actually made and whose data is used by the query is:

https://data.gov.uk/api/3/action/package_search?q=oranges

This means you can specify a base url that isn’t really just a base url just so that static analysis succeeds, and then use the Query option to construct the url you really want to use.

Of course this is all a bit of a hack and I’m sure, eventually, we’ll get to the point where any M code that works in Power BI Desktop and/or Power Query works in a published report. However it doesn’t sound as though this will be happening in the near future so it’s good to know how to work around this problem. I wonder whether there are other, similar tricks you can play with functions that access data sources apart from Web.Contents()? I need to do some testing…

UPDATE: The “Skip Test Connection” option on Power BI data sources, added in April 2019, solves some of the problems you run into where you can’t use RelativePath or Query to construct the url. See https://blog.crossjoin.co.uk/2019/04/25/skip-test-connection-power-bi-refresh-failures/

Using The RelativePath And Query Options With Web.Contents() In Power Query And Power BI M Code

The Web.Contents() function in M is the key to getting data from web pages and web services, and has a number of useful – but badly documented – options that make it easier to construct urls for your web service calls.

Consider the following url:

https://data.gov.uk/api/3/action/package_search?q=cows

It is a call to the metadata api (documentation here) for https://data.gov.uk/, the UK government’s open data portal, and returns a JSON document listing all the datasets found for a search on the keyword “cows”. You can make this call using Web.Contents() quite easily like so:

Web.Contents(
 "https://data.gov.uk/api/3/action/package_search?q=cows"
)

However, instead of having one long string for your url (which will probably need to be constructed in a separate step) you can use the RelativePath and Query options with Web.Contents(). They are given in the second parameter of the function and passed through as fields in a record. RelativePath adds some extra text to the base url given in the first parameter for the function, while Query allows you to add query parameters to the url, and is itself a record.

So, taking the example above, if the base url for the api is https://data.gov.uk/api we can use these options like so:

Web.Contents(
 "https://data.gov.uk/api", 
 [
  RelativePath="3/action/package_search", 
  Query=[q="cows"]
 ]
)

RelativePath is just the string “3/action/package_search” and is added to the base url. There is just one query parameter “q”, the search query, and the search term is “cows”, so Query takes a record with one field: [q=”cows”]. If you want to specify multiple query parameters you just need to add more fields to the Query record; for example:

Web.Contents(
	"https://data.gov.uk/api", 
	[
		RelativePath="3/action/package_search", 
		Query=
		[
			q="cows", 
			rows="20"
		]
	]
)

Generates a call that returns 20 results, rather than the default 10:

https://data.gov.uk/api/3/action/package_search?q=cows&rows=20

Obviously these options make it easier to construct urls and the code is much clearer, but there are also other benefits to using these options which I’ll cover in another blog post soon.

Note: at the time of writing there is a bug that causes the value given in RelativePath to be appended twice when the Web.Page() function is also used. Hopefully this will be fixed soon.

Handling 404–Not Found Errors With Web.Contents() In Power Query And Power BI

One strange feature of the Web.Contents() function in Power Query and Power BI is that it doesn’t respond in a consistent way to the standard error handling techniques used in M. I don’t know if this is a bug or a feature, but it’s certainly something I’ve run into a few times so I thought I would share a description of the problem and a way of working around it.

First of all, what’s the problem? Imagine that you wanted to import a list of training courses from that fine UK Microsoft BI and SQL Server training company Technitrain into Power Query or Power BI. You could do so using an M query that uses the Web.Contents() function to get the course RSS feed, like so:

let
    Source = Web.Contents("http://technitrain.com/feed/")
in
    Source

 

But what happens if you get the URL wrong, or there’s some other problem with the site? For example, the following URL will give a 404 – Not Found error because the page doesn’t exist:

http://technitrain.com/blahblah

If you use it in an M query, like so:

let
    Source = Web.Contents("http://technitrain.com/blahblah")
in
    Source

Unsurprisingly you get an error:

DataSource.Error: Web.Contents failed to get contents from ‘http://technitrain.com/blahblah’ (404): Not Found

image

The real issue is, though, when you attempt to handle this error with a try/otherwise statement like so:

let
    Source = try 
                Web.Contents("http://technitrain.com/blahblah") 
             otherwise 
                "Error!"
in
    Source

…it doesn’t work and you get the same error! What’s strange is that in some cases a try/otherwise block in more complex code will work, so for example in:

let
    Source = try 
                Xml.Tables(
                 Web.Contents("http://technitrain.com/blahblah")
                )
             otherwise 
                "Error!"
in
    Source

… the error does get caught:

image

This thread on the Power Query forum suggests it’s something to do with lazy evaluation, but I haven’t been able to determine the situations when it does work and when it doesn’t.

Instead, it is possible to handle specific HTTP error codes using the ManualStatusHandling option in Web.Contents():

let
    Source = Web.Contents(
    	"http://technitrain.com/blahblah",
    	[ManualStatusHandling={404}])
in
    Source

The ManualStatusHandling option takes a list of numeric HTTP error codes, and if you run the above example you’ll see that the query no longer returns an error.

The next problem is, then, how do you know whether the request worked or not? It turns out that you can find out by looking at the metadata associated with the Source variable (for some background on getting metadata values see this post). So, for example, using Value.Metadata() on the Source variable like so:

let
    Source = Web.Contents(
    	"http://technitrain.com/blahblah",
    	[ManualStatusHandling={404}]),
    GetMetadata = Value.Metadata(Source)
in
    GetMetadata

Returns a record which, among other things, contains the HTTP response code:

image

Therefore you can use something like the following pattern to trap 404 errors:

let
    Source = Web.Contents(
        "http://technitrain.com/blahblah",
        [ManualStatusHandling={404}]),
    GetMetadata = Value.Metadata(Source),
    GetResponseStatus = GetMetadata[Response.Status],
    Output = if GetResponseStatus=404 then "Error!" else Source
in
    Output

Using The “Skip Test Connection” Option For Power BI Data Sources To Avoid Scheduled Refresh Failures

One of the most popular blog posts I have written in recent years is this post on how the RelativePath and Query options for the Web.Contents() M function can be used to allow datasets that use web services as data sources to refresh successfully in the Power BI Service. It’s very frustrating when you write some complex M code in Power BI Desktop and find that your dataset can’t be refreshed after it has been published! While, at the time of writing, this problem is still present, yesterday’s announcement of the new “Skip Test Connection” option for data sources in the Power BI Service does mean there are more scenarios where your datasets can be made to refresh.

As I mentioned in that original post, the trick of using the RelativePath and Query options with Web.Contents() only works if the first parameter passed to Web.Contents() is a url that itself can be called on its own without an error. For example, the following expression:

Web.Contents(
	"http://www.myservice.com",
	[RelativePath="hello",
	 Query=[q="SearchTerm"]
	])

…will only refresh successfully in the Power BI Service if http://www.myservice.com can be reached as a url on its own without returning an error. I believe this is because this url is used when the Power BI Service is preparing to run the query to check whether the credentials it has stored are valid.  As the blog post says there is a workaround where dummy query parameter values can be used in that first parameter, but this won’t work in all cases. Instead, now you can turn on the “Skip Test Connection” option on the data source in the Power BI Service and the dataset will refresh even if http://www.myservice.com on its own returns an error.

Similarly this new option helps when you are using API keys passed in through query parameters for authentication. In Power BI Desktop and Excel Get&Transform/Power Query, you have the option to use the Web API authentication type to store sensitive API keys that need to be passed through url parameters securely rather than embed them in your M code. Unfortunately this is not supported in the Power BI Service yet and (as I found out on a recent consultancy engagement) there are other complications with using Anonymous authentication. For example, say you need to call a web service with an M expression something like this:

Web.Contents("http://www.myservice.com?key=password123")

…where the key query parameter contains an API key used for authentication. If you set this data source to use Anonymous authentication in Power BI Desktop or Excel it will refresh with no problems. However, after you publish to the Power BI Service you will not be able to refresh your dataset unless you turn on the “Skip Test Connection”, because the Power BI Service apparently strips out any query parameters from the url when it is testing the connection. In this case, if it strips out the key parameter, then obviously the call will fail because it has removed the means of authentication.

This new option does not mean every dataset can now be refreshed. As far as I can see, if you dynamically generate a url for use with Web.Contents() and do not use the RelativePath and/or Query options you will not be able refresh your dataset because the Power BI Service will not be able to analyse your code to discover what urls are present in it. I suspect that if you see the “Some data sources may not be listed because of hand-authored queries” warning in the Data Source Settings dialog in Power BI Desktop (which I blogged about here) then you will not be able to refresh your dataset in the Power BI Service, but I need to do more testing to be sure.

As always, if you test this yourself please let me know about any interesting things you find by leaving a comment!

Power BI, Caching, Parallelism And Power Query Refresh Performance

Some time ago a customer of mine (thank you, Robert Lochner) showed me a very interesting scenario where a set of Power Query queries in Power BI Desktop refreshed a lot faster with the “Enable Parallel Loading Of Tables” option turned off. This seemed a bit strange, but I have recently been reading lots of posts by Ehren von Lehe of the Power Query dev team on caching and query evaluation on the Power Query MSDN forum and two posts in particular, here and here, offered an explanation of what was going on. In this post I will walk through a very simple scenario that illustrates the information in that post and sheds some light on the internals of the Power Query engine.

Let’s say you have very simple web service built in Flow that, when it receives a GET request, waits 5 seconds and then returns the text “Hello”:

image

Here’s the M code for a Power Query query called SourceQuery that calls this web service and returns a table with one row and one column containing the text “Hello”:

let
    Source = Web.Contents("https://entermyurlhere.com"),
    ToLines = Lines.FromBinary(Source, null, null, 65001),
    ToTable = Table.FromColumns({ToLines})
in
    ToTable

image

Let’s also say you have four other identical queries called R1, R2, R3 and R4 that reference this query and do nothing but return the same table. Here’s the M code for these queries:

let
    Source = SourceQuery
in
    Source

Now, here’s the big question! If the output of SourceQuery is not loaded into Power BI but the output of R1, R2, R3 and R4 is loaded, as follows:

image

How many times would you expect the web service to be called when you refresh your dataset? One or four?

With the setting of “Enable Parallel Loading Of Tables” turned on, which is the default, the “Enable Data Preview To Download In The Background” setting turned off and Data Privacy checks turned off, Fiddler (see here for how to use it) shows the web service is called four times. SQL Server Profiler (see here for how to use it with Power BI) shows that the four queries are run in parallel and each query takes just over 5 seconds.

This seems wrong, because your natural inclination is to think that the Power Query engine evaluates SourceQuery first, and after that has happened the data passes from there to R1, R2, R3 and R4. In fact what happens is the reverse: R1, R2, R3 and R4 are evaluated in parallel and because each of them reference SourceQuery, then each of them causes SourceQuery to be evaluated independently. Yet another post by Ehren on the forum here explains this in detail.

The Power Query engine does do some caching in a ‘persistent cache’ that can be shared between queries and which stores the data requested from some types of data source on disk – it will store the data returned by Web.Contents for example, but not File.Contents – and only in some situations. The key statements about the persistent cache from this thread relevant to this particular problem are:

Power Query’s persistent cache (which stores data on disk during a particular refresh) is updated via a background thread. And separate evaluations (i.e. separate Microsoft.Mashup.Container.*.exe processes) running at the same time are not coordinated; when evaluation A is accessing the persistent cache (including updating it), this doesn’t block evaluation B from accessing the cache. This means that even when using a shared persistent cache, PQ can potentially end up requesting the same data twice. It depends on the timing of the various requests.

and

…you can reduce the number of evaluations happening at any given time (and thus the likelihood of timing-related cache misses, or additional unwanted requests) by doing the following:

  • Disabling background analysis (which pre-calculates the PQ Editor previews behind the scenes)
  • Disabling the Data Privacy Firewall (which does its own evaluations during refresh that could potentially cause duplicate requests, and also only consume a subset of the data in certain cases)

In PBIDesktop, you can also reduce the likelihood of timing-related cache misses by disabling parallel loading. (In Excel, the loading of multiple queries is always sequential)

As a result, with the “Enable Parallel Loading Of Tables” setting turned off, so the queries above are evaluated in series, Fiddler shows the web service is called only once. What’s more, Profiler shows that only one of the queries out of R1, R2, R3 and R4 takes just over five seconds while the other three, executed after it, are almost instant.

This must be because, when the queries are executed in series, the first query refreshes and data gets loaded into Power Query’s persistent cache. After that, even though the three subsequent queries also cause SourceQuery to be evaluated, each time SourceQuery is evaluated it can reuse the data stored in the persistent cache.

In contrast, with the four queries refreshed in parallel, each evaluation of SourceQuery takes place before the persistent cache has been populated and therefore the web service is called four times. This is slower, but in this case not much slower, than the scenario with the four queries executed in series – each query evaluation takes just over five seconds but remember that they are being executed in parallel so the overall duration is not much more than five seconds. In other cases the difference between parallel and sequential query execution could be a lot larger.

Now for the bad news: the “Enable Parallel Loading Of Tables” setting only works in Power BI Desktop, and there is no equivalent setting in the Power BI service. When a dataset is refreshed in the service, as far as I can tell the queries in the dataset are always evaluated in parallel. In Excel, as Ehren says, all queries are executed sequentially.

Is it possible to make sure the web service is called only once with all the queries executed in parallel? Yes, but not in a completely reliable way. The first thing to say here is that Table.Buffer and related buffering functions are not, as far as I understand it, useful here: they buffer data in memory within a single chain of execution, and in this case we have four separate chains of execution for R1, R2, R3 and R4. Instead what I have found that works is inserting a delay that gives the persistent cache time to be populated. If you keep the SourceQuery and R1 queries the same, and then alter the M code for R2, R3 and R4 so they wait for ten seconds (using Function.InvokeAfter) before returning as follows:

let
    Source = Function.InvokeAfter(
        ()=>SourceQuery, 
        #duration(0,0,0,10)
        )
in
    Source

 

In this particular case this results in the slowest refresh times and it only works because I can be sure that the call to the web service takes five seconds.

There’s one last thing to say here: wouldn’t it be nice if we could ensure that the web service was only called once, and all subsequent queries got their data from the a persisted copy of the data? As Matthew Roche points out here, this is exactly what dataflows allow you to do. Taking SourceQuery and turning it into an entity in a dataflow would result in a single call to the web service when the entity is refreshed, the data from the web service being persisted in the dataflow. You would then just need to have the queries R1, R2, R3 and R4 in your dataset, change them so they get their data from the entity in the dataflow, and as a result they would use the persisted copy of the data in the dataflow and would not call the web service. Another reason to use dataflows!

[I hope all the information in this post is correct  – it is based on Ehren’s forum posts and my own observations alone. If anyone from the Power Query dev team is reading this and spots an error, please let me know]

Power BI Data Privacy Levels And Cloud /Web-Based Data Sources Or Dataflows

UPDATE: it is now possible to set privacy levels for cloud data sources in the Power BI portal. See https://powerbi.microsoft.com/en-us/blog/privacy-levels-for-cloud-data-sources/

I have already blogged in great detail many times about Power BI/Power Query data privacy settings (see this series for example) but there’s always something new to learn. Recently I was asked a question by Ian Eckert about how Power BI handles data privacy for cloud or web-based data sources after a dataset has been published, and it prompted yet more revelations…

Consider the following M query:

let
    Source = Xml.Tables(
        Web.Contents("https://blog.crossjoin.co.uk/feed/")
        ),
    channel = Source{0}[channel],
    language = channel{0}[language],
    out = Json.Document(
        Web.Contents(
            "https://data.gov.uk/api",
            [
                RelativePath="3/action/package_search",
                Query=[q=language]
            ]
            )
            ),
    result = out[result],
    results = result[results],
    #"Converted to Table" = Table.FromList(
        results,
        Splitter.SplitByNothing(),
        null,
        null,
        ExtraValues.Error
        ),
    Column1 = #"Converted to Table"{0}[Column1],
    #"Converted to Table1" = Record.ToTable(Column1)
in
    #"Converted to Table1"

It doesn’t do anything particularly interesting, but it does take data from one web-based data source (the RSS feed for this blog) and sends it to another (the UK government’s open data metadata search web service). As a result, in Power BI Desktop, if you set the data privacy settings for both data sources to Public then the query runs, but if you set the data privacy settings for both data sources to Private:

image

image

…As expected, you get the following error:

image

Formula.Firewall: Query ‘Test’ (step ‘Converted to Table1’) is accessing data sources that have privacy levels which cannot be used together. Please rebuild this data combination.

Now the strange thing is that, when you publish the dataset that contains this M query, refresh always works. Why? What’s more, other datasets that do something similar will always fail when refreshed.

It turns out that when you publish a dataset that uses cloud or web-based data sources like the two used here, the Power BI service does not use the data privacy settings you have set in Power BI Desktop but instead it automatically assigns data privacy levels as follows:

  • Data sources, like the ones used here, that use Anonymous authentication are automatically given the privacy level Public
  • All other data sources are given the privacy level Private.

Interestingly, Power BI dataflows also count as cloud-based data sources and because they do not use Anonymous authentication they default to Private too, so if you are combining data from a dataflow with another data source in your dataset then you need to be careful of this.

What’s more there is at the time of writing no way to change these data privacy levels in the Power BI web-based portal. Hopefully this will change soon.

There are some workarounds though!

First of all, you can force refresh to take place through a gateway. This might sound strange because in theory, if you’re only using cloud or web-based data sources, a gateway should not be necessary. However there are already similar scenarios where a gateway is needed, for example if you are scraping data from a web page you need to use a gateway, and if you are combining data from a cloud-based data source with an on-premises data source you also need to use a gateway. If you add your cloud/web-based data sources as data sources in your gateway (unfortunately it does not seem to be possible to add a dataflow as a data source in a gateway, though) you can set their data privacy levels in the Advanced Settings section in the Manage Gateways screen:

image

You will also need to set the “Use a data gateway” option to On in the Settings dialog for your dataset after it has been published:

image

The other workaround is to copy the M code for your query and paste it into a new blank M query in an entity in a dataflow, as Matthew Roche shows here. While it does not seem to be possible to set data privacy levels for individual data sources when creating an entity, it is possible to turn off data privacy checks for an entity completely. If you create a query that sends data from one data source to another (regardless, as far as I can see, of the authentication mechanism used), you will see the following message in the Power Query Online query editor:

image

The evaluation was cancelled because combining data from multiple sources may reveal data from one source to another. Click Continue if the possibility of revealing data is okay.

If you click Continue, data privacy checks are turned off and the query runs; you can also click the Options button on the ribbon and check the “Allow combining data from multiple sources” option:

image

If one of your data sources is already itself a dataflow you may need to do some editing of the M query to make things work, but as Matthew Roche shows here it is possible to have an entity in a dataflow refer to another entity without using a computed entity (which is a Premium-only feature).

[Thanks to Arthi Ramasubramanian Iyer from Microsoft for providing background information for this post]

Fourteenth Blog Birthday

Every year, on the anniversary of the first-ever post on this blog, I write a post summarising my thoughts on what’s happening in the world of Microsoft BI and what I’m up to professionally.

This year, rather than go on about how Power BI is taking over the world (which we all know already), I thought it might be interesting to consider how the focus of this blog – and by implication the focus of my work – has changed over the last few years by looking at the viewing statistics of some of my most popular posts.

As you probably know, for a long time the only product I cared about was Analysis Services Multidimensional and MDX: it was pretty much all I blogged about and the only thing I did consultancy and training on. The following graph shows how the number of hits on four of the most-viewed posts on this subject from 2014 to 2018: Aggregating the result of an MDX calculation using scoped assignments; Joining the results of two MDX queries together; Last Ever Non Empty – a new, fast MDX approach; and One Cube vs Multiple Cubes.

image

 

None of these posts are, in technical terms, out of date but the downward trend is the same for all of them. The decline in traffic is matched by the decline in demand for consultancy and training on SSAS MD and MDX. While I still spend around 20% of my time doing SSAS MD and MDX consultancy, I do very little training on them at all these days – I guess because no-one is building new solutions using SSAS MD, although there are a still a large number of SSAS MD solutions in production that need maintenance and improvement. I expect the launch SSAS MD in the cloud as part of Power BI Premium will lead to a spike in the amount of work I do on it as I help my customers migrate but that will only be short-lived.

In contrast, look at the trend for four of my most-popular Power Query/M related posts: Referencing individual cell values from tables in Power QueryWorking with web services in Power Query; Creating tables in Power BI/Power Query M code using #table(); and Web.Contents(), M functions and dataset refresh errors in Power BI. These are not necessarily new posts (the earliest dates from 2014) but again they are all still technically relevant and the steep increase in the amount of hits over the last few years that they receive is clear:

image

Power Query and M is a bit of a niche topic, though; right now my most popular posts are on general Power BI data modelling and DAX – a topic I don’t actually blog about all that often, but which I nevertheless spend a lot of consultancy and training time on. The following graph shows the trends for the posts Comments and descriptions in DAX; Creating current day, week, month and year reports in Power BI using bi-directional cross-filtering and M; Dynamic chart titles in Power BI; and (although I’ve never really understood the popularity of this one) Using DateDiff() to calculate time intervals in DAX.

image

Perhaps I should blog about this more? The reason I don’t is twofold: first, there are a lot of people out there such as Marco and Alberto who specialise in DAX, have covered all the obvious angles and do a much better job than I ever could; second, my philosophy has always to blog about what I’m interested in and excited about, and frankly I have always enjoyed Power Query and M more than DAX.

One last graph is needed for context, showing the most popular posts from the three graphs above next to each other. The following graph shows how Aggregating the result of an MDX calculation using scoped assignments, Working with web services in Power Query and Dynamic chart titles in Power BI compare against each other:

image

It goes to show how the “Dynamic chart titles” post is now much more popular that the “Aggregating the result of an MDX calculation” post was, even at the peak of its popularity. I guess Power BI is a safe bet for my future.

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