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A pipe is a connector that links two elements in a PhixFlow model and sends data from the input to the output. Pipes allows you to control which attributes and which records from the input are delivered by to the output, although in most cases - with minimal configuration - you will get all columns and the records from the current run.

The pipe must be enabled to make it active.

For advanced configuration, see Advanced Pipe Configuration.

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A pipe joining a datasource to a data collector has no details to edit. All the configuration for the output data set occurs in the collector - either a database collector for a database datasource, or an HTTP collector for an HTTP datasource.

Basic Settings

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Enter a name. The name is used to refer to the pipe in other model elements. Pipe names default to in.

The name:

  • must start with a letter
  • must not be an Attribute Function name.
  • must not include special characters, except underscore _

...

Overview

A pipe is a connector that links two elements in a PhixFlow model and sends data from the input to the output. Pipes allows you to control which attributes and which records from the input are delivered by to the output, although in most cases - with minimal configuration - you will get all columns and the records from the current run.

The pipe must be enabled to make it active.

For advanced configuration, see Advanced Pipe Configuration.

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A pipe joining a datasource to a data collector has no details to edit. All the configuration for the output data set occurs in the collector - either a database collector for a database datasource, or an HTTP collector for an HTTP datasource.

Basic Settings

untickuntick when the pipe requests data from a non-static input stream, that stream will first attempt to bring itself up to date, generating new stream sets as necessary, before supplying the data requested.   to prevent the input stream from updating itself. The pipe will pull the existing data from the input stream.

Pipes from collectors cannot be marked as static.

   to indicate that, when multiple streams are being merged, there must be an input record from this pipe for an output record to be generated by the output stream.

If this is a push pipe with positive offsets and this option is ticked then the notification to create another stream set will only be pushed along the pipe if the last stream set created contains at least one record. This causes the pipe to present each candidate set to the output stream in a different way than usual.

 is the default. so that, for each output record generated by a stream, the stream will get a set of records from each of its input pipes. If the multiplier flag is ticked on one of these, then the stream will generate an output record for each record from the set of records provided by the multiplier pipe. For each output record, each of the other input pipes will provide the same set of records as normal.

Use this option to exclude or include input streams sets that have future dates relative to the stream set you are generating. For details about how future stream sets occur, see Managing Future Stream Sets, above.

 to exclude future stream sets from this analysis run. This is the default. to include future stream sets in this analysis run. For example, for a stream with Period: Transactional , you will want to include new streams sets that are being added to the input stream after your analysis run starts.
FieldDescription
Name

Enter a name. The name is used to refer to the pipe in other model elements. Pipe names default to in.

The name:

  • must start with a letter
  • must not be an Attribute Function name.
  • must not include special characters, except underscore _
Enabled

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 to prevent the pipe from being used during an analysis run.

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 to indicate the pipe properties are complete and the pipe is ready to be used. 

Static

Normally when a pipe requests data from a non-static input stream, that stream will first attempt to bring itself up to date, generating new stream sets as necessary, before supplying the data requested. However, if this field is ticked, the input stream will not run. Pipes from collectors cannot be marked as static.

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 when the pipe requests data from a non-static input stream, that stream will first attempt to bring itself up to date, generating new stream sets as necessary, before supplying the data requested.

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  to prevent the input stream from updating itself. The pipe will pull the existing data from the input stream.

Pipes from collectors cannot be marked as static.

Mandatory

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to indicate that, when multiple streams are being merged, there must be an input record from this pipe for an output record to be generated by the output stream.

If this is a push pipe with positive offsets and this option is ticked then the notification to create another stream set will only be pushed along the pipe if the last stream set created contains at least one record. This causes the pipe to present each candidate set to the output stream in a different way than usual.

Multiplier

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 is the default.

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ticked
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Mandatory
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Multiplier
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Type

Select:

  • Pull: pull pipes are the most common type in PhixFlow - they "pull" data from the input to the output. Pull pipes are shown as solid arrows on models.
  • Look-up: look-up pipes are used to enrich data. Typically, you will have one of more pull pipes to supply the base data for an output, and if needed one or more look-up pipes to enrich the base data with values from additional inputs. Look-up pipes are shown as dashed lines on models.
  • Push: data is "pushed" rather than "pulled" into the output stream. Push pipes are most commonly used when sending data from streams to exporters (File Exporters, Database ExportersHTTP Exporters). Push pipes are shown as dotted lines on models.
Data to Read

Select the type of input data to use.

  • Latest: supply data from the current run (the latest stream set). This is the mostly commonly used option.
  • Previous: supply data from the previous run (the previous stream set). This is used when you are comparing data for the current run with data from the previous run, for example, today's data with yesterday's.
  • All: supply data from all runs (all stream sets). 
  • All Previous: supply data from all runs except the current run (all stream sets except the latest stream set).
  • Same Run: this option should only be used where the input and output streams are set to Period: Transactional. The pipe will only collect data from inputs in the same analysis run. This configuration support several analysis runs going on at the same time without interfering with each other. 
  • Custom: select this option to display additional settings, described in the Custom Data to Read section, below. We recommend that you only use the custom settings when directed to by PhixFlow consultants or support.
Read Future Data
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Output

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In some circumstances the input stream may have stream sets that have dates in the future relative to the stream set being generated for the output stream. This may happen, for example, if:

  1. you roll-back some stream sets on the output stream
  2. but do not roll-back the corresponding stream sets on the input stream
  3. and then request that the output stream is brought up to date.

Some of the stream sets on the input stream will have dates in the future relative to some of the stream sets you are rebuilding.

By default, the Read Future Data checkbox is not ticked. This means pipes ignore any stream sets with dates in the future relative to the stream set you are generating. You want to ignore future stream sets when you rebuild an old stream set, because you want the pipe to retrieve the same data on the rerun as it retrieved when the stream set was first built.

When you run analysis on a stream with a transactional period, it is possible that as your analysis is still running, a different run can start and complete. This run can generate additional stream sets on the input stream with a future data relative to the date of the stream set you are generating. For transactional input streams, you want the pipe to use these future streams. To do this, tick the Read Future Data checkbox.

Filter

Filters are made up of a set of clauses; each clause in turn contains a number of conditions. These conditions must be satisfied for data to be passed through the pipe.

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Field

...

Description

...

Select one of the options

  • Where ALL...
  • Where ANY...

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Hover your mouse pointer over the Condition field to display this button.
Add another condition to your filter.

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Select an option from the list. PhixFlow adds more fields where you can:

  • select how the filter matches (for example, equals, contains, is null)
  • enter a string that the filter uses to match the data. The string can be an expression or a literal string.

...

Hover your mouse pointer over a filter clause to display this button.
Delete the selected clause or condition from the filter. 

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Indicates the value entered is a literal value. Click this icon to treat the value as an expression.

...

Indicates the value entered is an expression. Click this icon to treat the value to a literal string.

Note: ["123", "234", "345"] looks like a literal value but it can be evaluated as an expression.

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A cache extraction filter allows you to further filter the data retrieved by a pipe. These are not commonly used, but are sometimes helpful when either:

  • Optimising performance on a lookup pipe when for a set of records, the record you require from the lookup depends on non-key data, e.g. the date
  • When getting data from a pull pipe when the filter requires that you compare one value in each record with another; this is not possible within a standard filter.

For case 1, when using a lookup pipe, data retrieved is stored in a cache. See cache size for details. The cache extraction filter allows you, as you are processing a set of output records, to use different cached entries from the lookup for each of the records are you are processing. This is very fast compared to looking up from the source (i.e. going back to an external DB table or even another PhixFlow stream) for each output record.

E.g. you want to look up the credit rating for a customer for a set of transactions - in the output, each transaction is represented by a single output record.  You create an indexed lookup pipe using CustNo as the key for the index. This means that for each new CustNo you encounter in the data, all the credit rating entries for that CustNo would be retrieved by the pipe and placed into the cache. The credit rating for each customer is fully historied, so you get a number of entries for each CustNo. To get the relevant lookup entry for each output report (each transaction), you need to compare the transaction date of the output record to the dates of credit rating entries in the cache. So to extract the relevant record, you include a cache extraction filter in the form:

Code Block
StartDate >= _out.TransDate && (EndDate <= _out.TransDate || EndDate == _NULL)

Cache extraction filters are entered free hand.

The attribute names referenced must exist in a stream. This means that the each attribute must be one of:

  • an attribute in a source stream, if you are reading from a stream
  • if you are reading from an external database table, one of the fields returned by the database collector AND an attribute in the output stream. This means to use an attribute with the source as a database collector, there must be an attribute of matching name in the output stream
  • an attribute in the destination stream, in which case you will refer to it using the format _out.AttributeName

Filter Examples

Filter on Current User

Sometimes when running analysis you want to select, from the source, only records belonging to the currently logged in user. To set a filter where, say, an attribute in the source Owner equals the current logged in user, add a condition to the filter like this:

Owner Equals _user.name fx

Enter a list of values for an "Is In" or "Is Not In" filter

If you want to based on a list of values, use the Is in or Is not in comparators, then type the list of values into the comparison field as a comma separated list like this:

Country Is in England, France, Germany ABC

In this case you must NOT click the ABC icon to convert the value to an fx, because this will indicate that the value is a formula; it must be left as a literal value. If you do click the ABC icon, then the value must be entered like this:

Country Is in ["England","France","Germany"] fx

Sort/Group

Use this section to group and sort data as it comes through the pipe. for lookup pipes, this section is called Order/IndexThis section has:

  • a toolbar with standard buttons
  • a grid that lists the attributes that you want to sort or use to group
  • below the grid are the following options:

...

Enter an upper limit for grouped records.

When collating the input records into groups, PhixFlow uses the specified sort order. When it has added the maximum number of records, any more records for the group are ignored.

This can be useful if you want the most recent record for an attribute that has many records. 

  1. Tick the Group checkbox for the attribute you want to use for grouping.
  2. On an appropriate date attribute, apply a (Z-A) sort order.
  3. Set the Maximum Number of Records to 1. 

...

This field is available for pipes with the Type= Look-up.

Look-up pipes can be configured for fast "indexed" access to cached data collected from external tables, files or from other streams. Indexed access is controlled through configuring a pipe with an index and setting index expressions on grouping attributes. If the Type field on the Pipe is set to 'Look-up' then the field "Index Type" becomes available. This can have the value "None" meaning that there are no index keys or "Exact Match", "Best Match" or "Near Match" as described below:

...

Using the Sort/Group Grid

To add a stream attribute to the list:

...

For input stream attributes, PhixFlow displays the attribute name. (Read-only)

For a new attribute, enter a name.

...

Select the sort order

  • (A-Z) to sort data records in ascending order, e.g. A to Z, 1 to 9, earliest to latest date.
  • (Z-A) to sort data records in descending alpha-numeric order, e.g. Z to A, 9 to 1, latest to earliest date.

...

If this attribute is part of the candidate key set, you must tick the Group checkbox. Otherwise, the attributes will be used only to sort the data in the candidate set.

...

This field is available for lookup pipes with an Index Type option selected.

Look-up pipes can be configured for fast "indexed" access to cached data. This data is collected from external tables, files or from other streams. Indexed access is controlled through configuring a pipe with an index and setting index expressions on "Group By" attributes here.

...

Tip

In some cases, you may have a pipe connected to a database collector, which pulls data from an external database table. In these cases, the fields in the database must have matching attribute names in the output stream. You can refer to it using the format _out.AttributeName

Aggregate Attributes

Use this section to define the properties of data that you want to combine as it comes through the pipe.

Note

You cannot aggregate data from attributes if the pipe's input is from:

If you need to aggregate data from a database collector, you can use an SQL query. 

This section has:

  • a toolbar with standard buttons
  • a grid that lists the attributes that you want to aggregate.

...

 so that, for each output record generated by a stream, the stream will get a set of records from each of its input pipes. If the multiplier flag is ticked on one of these, then the stream will generate an output record for each record from the set of records provided by the multiplier pipe. For each output record, each of the other input pipes will provide the same set of records as normal.

Type

Select:

  • Pull: pull pipes are the most common type in PhixFlow - they "pull" data from the input to the output. Pull pipes are shown as solid arrows on models.
  • Look-up: look-up pipes are used to enrich data. Typically, you will have one of more pull pipes to supply the base data for an output, and if needed one or more look-up pipes to enrich the base data with values from additional inputs. Look-up pipes are shown as dashed lines on models.
  • Push: data is "pushed" rather than "pulled" into the output stream. Push pipes are most commonly used when sending data from streams to exporters (File Exporters, Database ExportersHTTP Exporters). Push pipes are shown as dotted lines on models.
Data to Read

Select the type of input data to use.

  • Latest: supply data from the current run (the latest stream set). This is the mostly commonly used option.
  • Previous: supply data from the previous run (the previous stream set). This is used when you are comparing data for the current run with data from the previous run, for example, today's data with yesterday's.
  • All: supply data from all runs (all stream sets). 
  • All Previous: supply data from all runs except the current run (all stream sets except the latest stream set).
  • Same Run: this option should only be used where the input and output streams are set to Period: Transactional. The pipe will only collect data from inputs in the same analysis run. This configuration support several analysis runs going on at the same time without interfering with each other. 
  • Custom: select this option to display additional settings, described in the Custom Data to Read section, below. We recommend that you only use the custom settings when directed to by PhixFlow consultants or support.
Read Future Data

Use this option to exclude or include input streams sets that have future dates relative to the stream set you are generating. For details about how future stream sets occur, see Managing Future Stream Sets, above.

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 to exclude future stream sets from this analysis run. This is the default.

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 to include future stream sets in this analysis run. For example, for a stream with Period: Transactional , you will want to include new streams sets that are being added to the input stream after your analysis run starts.

InputThe name of the object at the start of the pipe.
OutputThe name of the stream at the end of the pipe.

Anchor
future
future
Managing Future Stream Sets

In some circumstances the input stream may have stream sets that have dates in the future relative to the stream set being generated for the output stream. This may happen, for example, if:

  1. you roll-back some stream sets on the output stream
  2. but do not roll-back the corresponding stream sets on the input stream
  3. and then request that the output stream is brought up to date.

Some of the stream sets on the input stream will have dates in the future relative to some of the stream sets you are rebuilding.

By default, the Read Future Data check box is not ticked. This means pipes ignore any stream sets with dates in the future relative to the stream set you are generating. You want to ignore future stream sets when you rebuild an old stream set, because you want the pipe to retrieve the same data on the rerun as it retrieved when the stream set was first built.

When you run analysis on a stream with a transactional period, it is possible that as your analysis is still running, a different run can start and complete. This run can generate additional stream sets on the input stream with a future data relative to the date of the stream set you are generating. For transactional input streams, you want the pipe to use these future streams. To do this, tick the Read Future Data check box.

Filter

Filters are made up of a set of clauses; each clause in turn contains a number of conditions. These conditions must be satisfied for data to be passed through the pipe.

Tip

When the pipe Type is Lookup, the filter controls which data will be cached in memory.


Field
Description

Cache Size

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pipeCacheSize
pipeCacheSize


Available when Type is Lookup.

For lookup pipes, PhixFlow uses the pipe cache when it looks-up data from streams or database collectors. For efficiency, the records are cached (stored temporarily in memory) so that if the same set of records need to be looked up again they are readily available without going back to the database.

Enter a number to set a limit on the data cache size available for the pipe. You need to estimate the largest number of records that the lookup pipe will return on a single read. Check whether PhixFlow is looking up:

  • many records
    The pipe does a single lookup onto a stream or database table to get a large number of records in one go, for example 10,000 records.
  • few records may times
    The pipe does many lookups, getting a small number of records for each lookup, for example, 10 records at a time. In this case, PhixFlow is usually using a key value, such as an account number, to get the data. The key value is:
    • for a stream - the attribute used to filter the pipe
    • for a database collector - a condition in the database query. For example:
Code Block
WHERE AccountNumber = _out.AccountNum

If you do not set a limit for the cache, PhixFlow uses the system default set in System Configuration →  System Tuning → Maximum Pipe Cache Size.

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titleWarnings and Errors

In the log for an analysis run, which is available in the system console, PhixFlow reports warnings when a single read returns:

  • over 90% of the specified cache size
  • 100% or more of the cache size.

PhixFlow reports an error and stops the analysis run when:

  • a single read returns 100% or more of the cache size
  • and the System Configuration → Enforce Cache Size limit flag is ticked.

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titleError Message: Cache Size Limit Exceeded
The Pipe "stream_name.lookup_pipe_name" cache is 100% full (the cache size is 10).



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titleMore cache details

Every time the lookup pipe is referenced, PhixFlow calculates the values of all of the variable elements of the query or pipe filter, and checks if it already has a set of data in the cache retrieved using this set of variable values. If so the data is immediately returned from the cache. Otherwise, a new set of data is read from the stream of collector. If adding the new records to the cache would cause it to exceed the maximum cache size, previously cached results are removed to make enough room for the new results.


Pipe View

Use this option to look up data from attributes that are present in a stream view on the input stream.

Select a stream view from the list. If the input stream has no views, the list will be empty.

Note

Sorting or filtering of records must be set directly on the pipe. It is not inherited from the pipe view.

Use the pipe view to limit the attributes that the pipe reads when a stream has lots of attributes containing many data records but you only need data from a few attributes. Only the data for the attributes in the stream view are sent to the output stream.

Pipe views are very useful:

  • during lookups a pipe loads and caches all of the attributes from the stream. This can use a lot of memory, especially when there are many records. 
  • during file export all data records from all attributes are exported.

To set up a pipe view:

  1. Create a new view on the source stream. In the view, only add the attributes you need.
  2. In the pipe Pipe View option, select the pipe view.
  3. Run analysis. PhixFlow only looks-up or exports data from the attributes specified on the view.
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titleUsing pipe views with file exporters

If a File Exporter is configured to export to Excel or to HTML:

  • and it has an Excel template, PhixFlow uses this template and does not use any template specified in the pipe view.
  • but it does not have an Excel template, PhixFlow will use the Excel template specified in the pipe view (if there is one)
  • and the pipe view is a chart view, PhixFlow will export a PNG picture of the chart.


Include History Records

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 to filter out superseded records.

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 to include superseded records.

Condition

Select one of the options

  • Where ALL...
  • Where ANY...

To add more conditions, hover your mouse pointer over this field to display the  button and add another condition to your filter.

Clause

Select an option from the list. PhixFlow adds more fields where you can:

  • select how the filter matches (for example, equals, contains, is null)
  • enter a string that the filter uses to match the data. The string can be an expression or a literal string.
Filter Icons

Hover your mouse pointer over conditions or clauses to display:

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      another condition or clause to the filter
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     the selected clause or condition from the filter. 

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     indicates the value entered is a literal value. Click this icon to treat the value as an expression.
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    nopaneltrue
     indicates the value entered is an expression. Click this icon to treat the value to a literal string.
    Note: ["123", "234", "345"] looks like a literal value but it can be evaluated as an expression.

  • Image AddedOpen the expression in a larger editor.

Cache Extraction Filter

A cache extraction filter allows you to further filter the data retrieved by a pipe. These are not commonly used, but are sometimes helpful when either:

  • Optimising performance on a lookup pipe when for a set of records, the record you require from the lookup depends on non-key data, e.g. the date
  • When getting data from a pull pipe when the filter requires that you compare one value in each record with another; this is not possible within a standard filter.

For case 1, when using a lookup pipe, data retrieved is stored in a cache. See cache size for details. The cache extraction filter allows you, as you are processing a set of output records, to use different cached entries from the lookup for each of the records are you are processing. This is very fast compared to looking up from the source (i.e. going back to an external DB table or even another PhixFlow stream) for each output record.

E.g. you want to look up the credit rating for a customer for a set of transactions - in the output, each transaction is represented by a single output record.  You create an indexed lookup pipe using CustNo as the key for the index. This means that for each new CustNo you encounter in the data, all the credit rating entries for that CustNo would be retrieved by the pipe and placed into the cache. The credit rating for each customer is fully historied, so you get a number of entries for each CustNo. To get the relevant lookup entry for each output report (each transaction), you need to compare the transaction date of the output record to the dates of credit rating entries in the cache. So to extract the relevant record, you include a cache extraction filter in the form:

Code Block
StartDate >= _out.TransDate && (EndDate <= _out.TransDate || EndDate == _NULL)

Cache extraction filters are entered free hand.

The attribute names referenced must exist in a stream. This means that the each attribute must be one of:

  • an attribute in a source stream, if you are reading from a stream
  • if you are reading from an external database table, one of the fields returned by the database collector AND an attribute in the output stream. This means to use an attribute with the source as a database collector, there must be an attribute of matching name in the output stream
  • an attribute in the destination stream, in which case you will refer to it using the format _out.AttributeName

Filter Examples

Filter on Current User

Sometimes when running analysis you want to select, from the source, only records belonging to the currently logged in user. To set a filter where, say, an attribute in the source Owner equals the current logged in user, add a condition to the filter like this:

Owner Equals _user.name fx

Enter a list of values for an "Is In" or "Is Not In" filter

If you want to based on a list of values, use the Is in or Is not in comparators, then type the list of values into the comparison field as a comma separated list like this:

Country Is in England, France, Germany ABC

In this case you must NOT click the ABC icon to convert the value to an fx, because this will indicate that the value is a formula; it must be left as a literal value. If you do click the ABC icon, then the value must be entered like this:

Country Is in ["England","France","Germany"] fx

Sort/Group

For lookup pipes this section is called Order/Index.

Use this section to group and sort data as it comes through the pipe. This section has:

  • a toolbar with standard buttons
  • a grid that lists the attributes that you want to sort or use to group
  • below the grid are the following options:
FieldDescription
Maximum Number of records per Group

Enter an upper limit for grouped records.

When collating the input records into groups, PhixFlow uses the specified sort order. When it has added the maximum number of records, any more records for the group are ignored.

This can be useful if you want the most recent record for an attribute that has many records. 

  1. Tick the Group check box for the attribute you want to use for grouping.
  2. On an appropriate date attribute, apply a (Z-A) sort order.
  3. Set the Maximum Number of Records to 1. 
Index Type

Available when Type is Look-up.

Look-up pipes can be configured for fast "indexed" access to cached data collected from external tables, files or from other streams. Indexed access is controlled through configuring a pipe with an index and setting index expressions on grouping attributes. If the Type field on the Pipe is set to 'Look-up' then the field "Index Type" becomes available. This can have the value "None" meaning that there are no index keys or "Exact Match", "Best Match" or "Near Match" as described below:

  • Exact Match: The pipe retrieves data from its cache based on an exact match look-up with the values provided after evaluating the index expressions on the "Group By" attributes.

  • Best Match: The pipe retrieves data from its cache based on a "Best Match" look-up after evaluating the index expressions on the "Group By" attributes.
    Note: The last Group By Attribute with a key expression is used for the best match lookup. The index keys on any Group By attributes with a lower sequence number are used as an initial "Exact Match" to find the set of data on which to do the "Best Match". The "Best Match" is defined as the longest key value which matches the evaluated index expression.

  • Near Match: The pipe will retrieve data from its cache based on a "Near Match" look-up after evaluating the index expressions on the "Group By" attributes.
    Note: the last Group By Attribute with a key expression is used for the near match lookup. The index keys on any Group By attributes with a lower sequence number are used as an initial "Exact Match" to find the set of data on which to do the "Best Match". When "Near Match" is selected, an additional field appears where you can enter an expression which should evaluate to a number representing the allowed number of edits (e.g. deletions, insertions, substitutions and transpositions) which can be made when comparing the result of the index expression to the index key in order to achieve a match. For example if the index key is "Smyhte" and the result of the index expression is "Smith" this would still be a match providing that the allowed number of edits is 3 or more (i.e. substitute the 'i' for a 'y', transpose the 't' and the 'h' and then insert an 'e' at the end).

Using the Sort/Group Grid

To add a stream attribute to the list:

  • click 
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     to open the list of attributes in the input stream
  • drag a stream attribute into the grid.

To remove an attribute, click 

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 in the toolbar.

To set the sort or group properties for an aggregate attribute, double-click its name in the grid. PhixFlow opens the attribute's sort properties:

...

Select an function to combine stream data records.

  • Average
  • Count
  • Distinct
  • Maximum
  • Minimum
  • Sum

See Aggregate Function for details. Make sure the function matches the data in the attribute. For example, you cannot Sum text.

...

Select the stream attribute aggregated from the list of attributes in the input stream.

PhixFlow does not use the value in this field if the Aggregate Function is Count.

...

Advanced

...

This checkbox is available when the pipe Type is Push or Pull.

...

PhixFlow cannot complete a stream set if:

...

Tip

You must tick this checkbox on all the pipes that will read from a static (or effectively static) input stream in the analysis run. PhixFlow will report an error if there is any pipe trying to complete the stream set during the analysis run.

Pipes that are not used in the analysis run do not try to complete a stream set, so will not report an error. (Unused pipes can occur if they lead to streams on branches of the model that are not being run.)

...

Cache Size

...

Enter a number to set a limit on the data cache size available for the pipe. You need to estimate the largest number of records that the lookup pipe will return on a single read. Check whether PhixFlow is looking up:

  • many records
    The pipe does a single lookup onto a stream or database table to get a large number of records in one go, for example 10,000 records.
  • few records may times
    The pipe does many lookups, getting a small number of records for each lookup, for example, 10 records at a time. In this case, PhixFlow is usually using a key value, such as an account number, to get the data. The key value is:
    • for a stream - the attribute used to filter the pipe
    • for a database collector - a condition in the database query. For example:
Code Block
WHERE AccountNumber = _out.AccountNum

If you do not set a limit for the cache, PhixFlow uses the system default set in System Configuration →  System Tuning → Maximum Pipe Cache Size.

...

titleWarnings and Errors

In the log for an analysis run, which is available in the system console, PhixFlow reports warnings when a single read returns:

  • over 90% of the specified cache size
  • 100% or more of the cache size.

PhixFlow reports an error and stops the analysis run when:

...

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titleError Message: Cache Size Limit Exceeded
The Pipe "stream_name.lookup_pipe_name" cache is 100% full (the cache size is 10).
Expand
titleMore cache details

Every time the lookup pipe is referenced, PhixFlow calculates the values of all of the variable elements of the query or pipe filter, and checks if it already has a set of data in the cache retrieved using this set of variable values. If so the data is immediately returned from the cache. Otherwise, a new set of data is read from the stream of collector. If adding the new records to the cache would cause it to exceed the maximum cache size, previously cached results are removed to make enough room for the new results.

...

Use this option to look up data from attributes that are present in a stream view on the input stream

Select a stream view from the list. If the input stream has no views, the list will be empty.

Note

Sorting or filtering of records must be set directly on the pipe. It is not inherited from the pipe view.

Use the pipe view to limit the attributes that the pipe reads when:

  • a stream has lots of attributes containing many data records 
  • but you only need data from a few attributes.

Only the data for the attributes in the stream view are sent to the output stream.

Pipe views are very useful:

  • during lookups a pipe loads and caches all of the attributes from the stream. This can use a lot of memory, especially when there are many records.
  • during file export all data records from all attributes are exported.

To set up a pipe view:

  1. Create a new view on the source stream. In the view, only add the attributes you need.
  2. In the pipe Pipe View option, select the pipe view.
  3. Run analysis. PhixFlow only looks-up or exports data from the attributes specified on the view.

...

titleUsing pipe views with file exporters

If a File Exporter is configured to export to Excel or to HTML:

...

If you want to create a new attribute that is not present in the input stream, in the section toolbar, click

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. PhixFlow opens the attribute's sort properties:

FieldDescription
Attribute

For input stream attributes, PhixFlow displays the attribute name. (Read-only)

For a new attribute, enter a name.

OrderEnter the number for the order the attribute appears in the grid and the order in which it is processed. Other attributes are renumbered.
Direction

Select the sort order

  • (A-Z) to sort data records in ascending order, e.g. A to Z, 1 to 9, earliest to latest date.
  • (Z-A) to sort data records in descending alpha-numeric order, e.g. Z to A, 9 to 1, latest to earliest date.
Group

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 by default, data is not grouped.

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 to group data records by the value in this attribute.

If this attribute is part of the candidate key set, you must tick the Group check box. Otherwise, the attributes will be used only to sort the data in the candidate set.

Index Expression

This field is available for lookup pipes with an Index Type option selected.

Look-up pipes can be configured for fast "indexed" access to cached data. This data is collected from external tables, files or from other streams. Indexed access is controlled through configuring a pipe with an index and setting index expressions on "Group By" attributes here.

Audit SummarySee Common Properties.


Tip

In some cases, you may have a pipe connected to a database collector, which pulls data from an external database table. In these cases, the fields in the database must have matching attribute names in the output stream. You can refer to it using the format _out.AttributeName

Aggregate Attributes

Use this section to define the properties of data that you want to combine as it comes through the pipe.

Note

You cannot aggregate data from attributes if the pipe's input is from:

If you need to aggregate data from a database collector, you can use an SQL query. 

This section has:

  • a toolbar with standard buttons
  • a grid that lists the attributes that you want to aggregate.

Using the Aggregate Attributes Grid

To add a stream attribute to the list:

  • click 
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     to open the list of attributes in the input stream
  • drag a stream attribute into the grid.

To remove an attribute, click 

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 in the toolbar.

To set the properties for an aggregate attribute, double-click its name in the grid. PhixFlow opens the attribute's sort properties:

FieldDescription
Stream Function

Select an function to combine stream data records.

  • Average
  • Count
  • Distinct
  • Maximum
  • Minimum
  • Sum

See Aggregate Function for details. Make sure the function matches the data in the attribute. For example, you cannot Sum text.

Attribute

Select the stream attribute aggregated from the list of attributes in the input stream.

PhixFlow does not use the value in this field if the Aggregate Function is Count.

NameEnter the name for the aggregated attribute. This can be the same as the original attribute.
OrderThe order of the aggregate attribute in the output stream.

Advanced

The following options are available when the pipe Type is Push or PullAllow Incomplete Stream Sets is also available when the pipe Type is Lookup.

FieldDescription
Data Expected

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 means the pipe may receive no data from its input during an analysis run.

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  means PhixFlow reports an error if the pipe receives no data from the input datasource, collector or stream during an analysis run.

Allow Incomplete Stream Sets

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 to complete a stream set before passing the data to the output stream. During the analysis run, PhixFlow pulls data into the input stream until the stream set is complete. If it cannot complete the stream set, PhixFlow reports an error message.

PhixFlow cannot complete a stream set if:

  • either the input stream is set to be  
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  • or all of the pipes reading from the stream are static.

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  PhixFlow ignores incomplete stream sets in a static input stream and does not report an error.

Tip

You must tick this check box on all the pipes that will read from a static (or effectively static) input stream in the analysis run. PhixFlow will report an error if there is any pipe trying to complete the stream set during the analysis run.

Pipes that are not used in the analysis run do not try to complete a stream set, so will not report an error. (Unused pipes can occur if they lead to streams on branches of the model that are not being run.)

Buffer SizeEnter a number for the buffer size used to perform the stream calculation. If a large amount of data is being processed, then setting a large buffer size will give better performance.

Max Records To Read


Enter a number for the maximum number of records that should be read down this pipe. The pipe may read more than this number of records if it is configured to carry out multiple reads simultaneously. For example:

  • a pipe can be  connected to a File Collector that reads multiple files simultaneously
  • the pipe strategy is Directed with multiple workers.
Strategy

Select an option to specify how this pipe should be implemented. See the section on Directed Merge Strategy

Max Workers

This field is available when Strategy is Directed

Enter the maximum number of concurrent worker tasks. When no value is specified, this defaults to 1.

Worker Size

This field is available when Strategy is Directed

Enter the number of key values to read for a single worker task, which runs a single select statement.

When no value is specified, this defaults to 1000. This is the maximum value that can be used when reading from an Oracle database.

Custom Data to Read

Data to Read = Custom

The following fields are available in the Basic Settings section if you set Data To Read = Custom:

In almost all cases this specifies the number of stream sets to be retrieved from the input stream. However, if this is a push pipe with positive offsets this value indicates the maximum number of stream sets that can be created i.e. the maximum number of cycles this pipe can initiate.
FieldDescription
From OffsetThe offset applied to the start of the collection period, relative to the period in the output stream that requires populating.
To OffsetThe offset applied to the end of the collection period, relative to the period in the output stream that requires populating.
Max Stream Sets

Log Traffic

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  • Pipe Logging: when ticked, PhixFlow always logs the number of records returned by this pipe, whatever is set here.

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Custom Data to Read 
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custom

The following properties are available in Basic Settings when you set Data To Read to Custom.

If this flag is ticked then use this flag is are transactional

Use this option to exclude or include input streams sets that have future dates relative to the stream set you are generating. For details about how future stream sets occur, see Managing Future Stream Sets, above.

FieldDescription
Only collect from same run

Every time the analysis engine runs, all of the stream sets that are created by all of the streams affected by that analysis run are given the same Run ID.

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 so the pipe can collect stream sets with different Run IDs.

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 so that the pipe will only collect stream sets from the input stream that have the same Run ID as the stream set currently being created by the output stream. You should only

tick this check box if both the input and output streams

have Period set to Transactional.

HistoriedIf ticked, the pipe will collect data from the input stream by period. So if the from and to offsets are both 0.0, and the output stream requires stream generation for the period 17/10/07 - 18/10/07, data will be collected from the input stream for the period 17/10/07 - 18/10/07. If not ticked, all data will be collected from the input stream, regardless of period. In this case, the offsets are still used to determine whether the required data periods in the input stream exist before the stream calculation can be carried out.
Read Future DataFrom OffsetEnter the offset applied to the start of the collection period, relative to the period in the output stream that requires populating.
To OffsetEnter the offset applied to the end of the collection period, relative to the period in the output stream that requires populating.
Max Stream Sets

Enter the number of stream sets to be retrieved from the input stream. 

For a push pipe with positive offsets. enter the maximum number of stream sets that can be created i.e. the maximum number of cycles this pipe can initiate.

Historied

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 to exclude future stream sets from this analysis run. This is the default  so that all data will be collected from the input stream, regardless of period. In this case, any From Offset or To Offset values determine whether the required data periods in the input stream exist before the stream calculation can be carried out.

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 to include future stream sets in this analysis run. For example, for a stream with Period: Transactional , you will want to include new streams sets that are being added to the input stream after your analysis run starts. so that the pipe will collect data from the input stream by period.

For example, if:

  • the from and to offsets are both 0.0
  • and the output stream requires stream generation for the period 17/10/07 - 18/10/07

the pipe reads data from the input stream for the period 17/10/07 - 18/10/07.