MashZone NextGen Analytics : Working with MashZone NextGen Analytics In-Memory Stores : Store Data in MashZone NextGen Analytics In-Memory Stores : Append Query Results Repeatedly
Append Query Results Repeatedly
In cases where a source dataset is regularly updated, updates can be appended to the existing data in the In-Memory Store.
The following example mimics time-based updates by appending rows to an existing In-Memory Store using the EMML <foreach> statement. This statement loops through the Manufacturing Plants dataset (introduced in ) and selects rows for a given country. These rows are then appended to an existing In-Memory Store named storeAppendPlants.
The example then pauses to ensure that the rows appended are distinct based on their timestamp, as shown in this example of the results:
Some points to keep in mind in this example:
*The first loop of this mashup creates the In-Memory Store the first time the mashup is run.
*Every row stored has a column added with the timestamp when the row was added. For more information on timestamps in the In-Memory Store, see About Row Timestamps for Stored Datasets.
*The JavaScript function in this example is used solely for effect, to ensure distinctly different timestamps for each append to the In-Memory Store.
Note:  
This In-Memory Store is also used in the Load Dataset Rows for Specific Time Periods example to illustrate loading data based on row timestamps.
The complete EMML code for this example is shown here.
Note:  
Be aware that this mashup will take over 50 seconds to run because of the deliberate pauses.
<mashup xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance'
xsi:schemaLocation='http://www.openmashup.org/schemas/v1.0/EMML/../schemas/EMMLSpec.xsd'
xmlns='http://www.openmashup.org/schemas/v1.0/EMML'
xmlns:macro='http://www.openmashup.org/schemas/v1.0/EMMLMacro'
name='storeAppend'>
<output name='result' type='document' />
<variable name="plants" type="document" subType="csv"/>
<!-- Countries to interate over -->
<variable name="countries" type="document">
<countries>
<country>BELGIUM</country>
<country>CANADA</country>
<country>FRANCE</country>
<country>INDIA</country>
<country>ITALY</country>
<country>JAPAN</country>
<country>NETHERLANDS</country>
<country>SPAIN</country>
<country>SWEDEN</country>
<country>UNITED KINGDOM</country>
</countries>
</variable>
<variable name="searchFor" type="string" />
<!-- Loop for each country, retrieve plants for country and append to
in-memory store, pause 5 seconds so timestamps are distinct -->
<foreach variable='location' items='$countries/countries/country' >
<variable name="found" type="document" stream="true"/>
<assign fromexpr="$location/text()" outputvariable="$searchFor"/>
<directinvoke method='GET' stream='true' outputvariable='plants'
endpoint='http://mdc.jackbe.com/prestodocs/data/mfgplants.csv' />

<raql stream="true" outputvariable='found'>
select Country, Name, Active_Production_Lines,
Production_Lines_Under_Construction from plants
where Country = '{$location}'
</raql>
<storeto cache='storeAppendPlants' key='#unique' variable='found' />
<script type='text/javascript' outputvariable="result">
<![CDATA[
function pause(millis){
var date = new Date();
var curDate = null;

do { curDate = new Date(); }
while(curDate-date < millis);
}
pause(5000);
]]>
</script>
</foreach>
</mashup>
About Row Timestamps for Stored Datasets
In addition to keys, RAQL adds a timestamp to each row of a dataset for the date and time that row was added to the In-Memory Store. In some cases, datasets already have a column with a timestamp related to the original source of the data.
Because of potential name conflicts, the actual column name for the In-Memory Store timestamp, varies based on the dataset in question and the storage mode (append or overwrite):
If Existing Dataset
And Store Mode is
In-Memory Store Timestamp Column
Has no column named timestamp.
Overwrite or append.
timestamp
Has a column named timestamp.
Append rows to an existing dataset key.
timestamp
In this case, the timestamp for the In-Memory Store will overwrite the original source timestamp, unless you provide an alias for the original column.
Overwrite existing dataset.
_timestamp
Copyright © 2013-2016 Software AG, Darmstadt, Germany.

Product LogoContact Support   |   Community   |   Feedback