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.

For information about the properties toolbar, and about the sections Parent Details, Analysis Models, Description and Audit Summary, see Common Properties. For a full list of all the PhixFlow property tabs and windows, see Property Tabs.

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

Field	Description
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	Untick to prevent the pipe from being used during an analysis run. Tick 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. Untick 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. Tick 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	Untick Tick 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	Untick is the default. Tick 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 Exporters, HTTP 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. Untick to exclude future stream sets from this analysis run. This is the default. Tick 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.
Output

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:

you roll-back some stream sets on the output stream
but do not roll-back the corresponding stream sets on the input stream
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.

Field	Description
Include History Records	Untick to filter out superseded records. Tick 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 Add button.
Add	Hover your mouse pointer over the Condition field to display this button. 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.
Permanently Delete	Hover your mouse pointer over a filter clause to display this button. Delete the selected clause or condition from the filter.
(literal string)	Indicates the value entered is a literal value. Click this icon to treat the value as an expression.
(expression string)	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.
	Open 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: 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/Index. 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:

Field

Description

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.

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

Index Type

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:

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 attributes to the list:

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

To remove an attribute, click Permanently Delete in the toolbar.

To set the sort or group properties for an attribute, double-click its name in the grid. If you want to create a new attribute that is not present in the input stream, in the section toolbar, click Add. PhixFlow opens the attribute's sort properties:

Field	Description
Attribute	For input stream attributes, PhixFlow displays the attribute name. (Read-only) For a new attribute, enter a name.
Order	Enter 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	Untick by default, data is not grouped. Tick 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 checkbox. 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 Summary	See Common Properties.

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

Aggregate Attributes define the aggregated properties that are available when data is read from an aggregating Pipe. Note that Aggregate Attributes are not available on Pipes from Database Collectors (any aggregation can be performed in the query SQL), nor are they available on Pipes from File Collectors.

Possible aggregate values are counts, summations, averages and maximum or minimum values of Stream Items grouped in the Group/Order tab of the Pipe.

Use this section to combine data from different attributes it comes through the pipe. This section has:

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

.

Aggregate Attributes define the aggregated properties that are available when data is read from an aggregating Pipe. Note that Aggregate Attributes are not available on Pipes from Database Collectors (any aggregation can be performed in the query SQL), nor are they available on Pipes from File Collectors.

Possible aggregate values are counts, summations, averages and maximum or minimum values of Stream Items grouped in the Group/Order tab of the Pipe.

Field	Description
Stream Function	The Aggregate Function e.g. Count or Sum.
Attribute	The name of the Stream Attribute to be aggregated. Note that the value in this field is not used if the Aggregate Function is Count.
Name	A new name for the aggregated attribute. Note that this can be the same as the original Attribute.
Order	The order of the aggregate attribute.

Only aggregate attributes which can be aggregated. For example, do not try to sum an attribute which contains text.

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:

Field	Description
From Offset	The offset applied to the start of the collection period, relative to the period in the output stream that requires populating.
To Offset	The offset applied to the end of the collection period, relative to the period in the output stream that requires populating.
Max Stream Sets	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.
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. If this flag is ticked then 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 use this flag is both the input and output streams are transactional.
Historied	If 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 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. Untick to exclude future stream sets from this analysis run. This is the default. Tick 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.

Advanced section

The following fields are configured in the Advanced section:

Field	Description
Data Expected	This field is available when the Pipe Type is Push or Pull. This flag allows the user to specify that the pipe is expecting to receive data. If ticked but no data is received this is treated as an error.
Allow Incomplete Stream Sets	Normally, when a pipe tries to read from an input stream that contains an incomplete stream set, PhixFlow will attempt to complete the stream set before passing data down the pipe. However if the stream is static (i.e. the stream has its 'static' flag ticked) or is effectively static (i.e. all of the pipes reading from it in this analysis run are static) then, instead of completing the stream set, an error message is produced indicating that you cannot read from this stream because it contains an incomplete stream set. If you do not want this error message to be produced when reading from static (or effectively static) streams, but would instead prefer PhixFlow to ignore the incomplete stream sets, then you must tick this box on all pipes that will read from the input stream in this analysis run. If there are multiple pipes that read from the input stream during this analysis run and even one of the pipes does not have this box ticked then you will not be allowed to read from the stream and the error message will be produced. Pipes which are not used in the current analysis run (for example where they lead to streams on branches of the model which are not run by the current task plan) have no effect on whether or not the error message is produced.
Cache Size	The cache is used when carrying out lookups from streams or database collectors. When doing a lookup, there are two common scenarios: The pipe does a single lookup onto a stream or database table to get a large number of records in one go (e.g. 10,000 records) The pipe does many lookups, getting a small number of records for each lookup (e.g. 10 records at a time). In case 2, the results returned are typically based on a key value, e.g. an account number. This will be used in the filter of the pipe, if you are reading from a stream, or in the query, if you are reading from a database collector. For example, the query in a database collector will include the condition: WHERE AccountNumber = _out.AccountNum 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. This field allows you to set a limit on the size of the cache. Setting a limit is important because if you do not, the cache can become very large and consume a lot of memory, which can lead to a slow down in both your tasks and those of other users of PhixFlow. To set the cache size, try to estimate the largest number of records that the lookup pipe will return on a single read. If you do not set a limit, it will default to the system-wide default, specified in the Maximum Pipe Cache Size in the System Tuning tab of the System Configuration. Cache warnings and errors If a single read brings back over 90% of the specified cache size, a warning message will be logged to the console. If a single read brings back 100% or more of the cache size, a second warning message will be generated. If the Enforce Cache Size limit flag is ticked in System Configuration, instead of a warning an error will be generated, and the analysis run will stop completely. Error Message: Cache Size Limit Exceeded The Pipe "stream_name.lookup_pipe_name" cache is 100% full (the cache size is 10). Technical breakout 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.
Buffer Size	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.
Pipe View	The pipe view is used to limit which fields are retrieved down the pipe and in what order, and in some circumstances how each field is to be formatted. You can select from any of the views that have been configured on the source stream. Please note that any sorting or filtering of records will have to be applied directly on the pipe, and will not be inherited from the pipe view. The pipe view is used in two contexts. During lookups Pipe views can also be used on lookup pipes to limit the fields that are returned by the lookup request. This is most useful in the scenario where the you want to read and cache data on a lookup pipe from a stream that has lots of attributes but where only a small number of attributes are actually required. You can simply create a new view on the source stream listing only the attributes needed, then specify it as the pipe view on the lookup pipe. Only those attributes specified on the view will then be loaded. Without a pipe view, the pipe will load and cache all of the attributes from the stream which may consume a significant amount of free memory if there are a large number of records. During File Export When sending data to a file exporter only those fields specified on the pipe view will be exported. If no pipe view is supplied then all fields will be exported. If the file exporter is configured to export to Excel or to HTML, and no Excel template is specified on the exporter, then the pipe view will be checked to see if an Excel template has been specified there. This template will then be used as part of the export. See the description of file exporters for further details. If an Excel template has been specified on the exporter then this will override any template specified on the pipe view. If the file exporter is configured to export to HTML and the pipe view is a chart view then the output will be a picture of the chart in PNG format.
Max Records To Read	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 e.g. if it is connected to a File Collector which has been configured to read multiple files simultaneously or if this pipe strategy is "Directed" with multiple workers.
Strategy	The Execution Strategy determines how this pipe should be implemented. See the section on Directed Merge Strategy
Max Workers	This field is only available if Strategy = Directed The maximum number of concurrent worker tasks. If blank, this defaults to 1.
Worker Size	This field is only available if Strategy = Directed The number of key values to read for a single worker task (which runs a single select statement). If blank, this defaults to 1000. This is the maximum value that can be used when reading from an Oracle database.

Pipe