Monday, November 26, 2012

OBIEE Patch Released

OBIEE (aka BP6) is out and until MOS hosts a proper tracking note, here is the list of all patches making up this patch set with direct links.

Patch 15844023    Patch (1 of 7) Oracle Business Intelligence Installer
Patch 15844066    Patch (2 of 7) Oracle Real Time Decisions
Patch 14800665    Patch (3 of 7) Oracle Business Intelligence Publisher
Patch 15843961    Patch (4 of 7) Oracle Business Intelligence ADF Components
Patch 15844096    Patch (5 of 7) Enterprise Performance Management Components Installed from BI Installer
Patch 14791926    Patch (6 of 7) Oracle Business Intelligence
Patch 15839347    Patch (7 of 7) Oracle Business Intelligence Platform Client Installers and MapViewer

As always: don't forget JDEV patch 13952743


Tuesday, October 30, 2012


While I was off, Oracle released OBIEE which is another bugfixing patch set which doesn't bring in new functionality but irons out quite a few quirks.

Here you can find the main MOS article detailling the patches making up this patch set as all bugs fixed in it.

By the way...make sure you don't forget JDEV patch 13952743.


Tuesday, August 14, 2012

D3.js calendar configuration in OBIEE 11g

With the release of the BP1 SampleApp V207, I’ve taken a moment to dissect the usage of the D3.js calendar contained within since it is one of the examples frequently pointed out to showcase new visualisation capabilities.

Let's dive a bit deeper into this to understand the way the D3 calendar works and what is necessary to embed this in any other OBIEE installation.

As-Is in SampleApp:

Checking the Answers Criteria block, the analysis is quite straight-forward. “Color Low” and “Color High” being simply presentation variables grabbing the values passed from the “Red / Green Color Limit” prompts on the dashboard page.

The actual functionality of the D3 calendar is contained and controlled by the two narrative views of the analysis which I will be calling the “Context Narrative” and “Content Narrative” respectively for the purpose of this post:

Context narrative:

Key here are the four JavaScript variables which will be used by the code within the content narrative below. These are filled by the values collected from the 1st line of the analysis data set (Rows to display = 1). Generally, when analysing the D3.js examples, it is hugely helpful to add a simple table view to the analysis in order to see what the data stream actually brings along from the OBI server since most examples use mixtures of column references and variables.

VERY IMPORTANT: year_range2 must always be the end year +1!
You don’t have to provide these values through dashboard prompts and simply read the from the data set, but having a means to restrict the data displayed is always comfortable.

Content narrative:


<script type="text/javascript" src="/analyticsRes/d3/d3.v2.js"></script>
    <link type="text/css" rel="stylesheet" href="/analyticsRes/d3/lib/colorbrewer/colorbrewer.css"/>
    <link type="text/css" rel="stylesheet" href="/analyticsRes/d3/examples/calendar/calendar.css"/>

    <div id="my_chart"></div>
    <script type="text/javascript">
var margin = {top: 19, right: 20, bottom: 20, left: 19},
    width = @{Width}{720}- margin.right - margin.left, // width
    height = @{Height}{136} - - margin.bottom, // height
    cellSize = @{CellSize}{12}; // cell size

var day = d3.time.format("%w"),
    week = d3.time.format("%U"),
    percent = d3.format(".1%"),
    format = d3.time.format("%Y-%m-%d");

var color = d3.scale.quantize()

var svg ="#my_chart").selectAll("svg")
    .data(d3.range(year_range1, year_range2))
    .attr("width", width + margin.right + margin.left)
    .attr("height", height + + margin.bottom)
    .attr("class", "RdYlGn")
    .attr("transform", "translate(" + (margin.left + (width - cellSize * 53) / 2) + "," + ( + (height - cellSize * 7) / 2) + ")");
    .attr("transform", "translate(-6," + cellSize * 3.5 + ")rotate(-90)")
    .attr("text-anchor", "middle")
var rect = svg.selectAll("")
    .data(function(d) { return d3.time.days(new Date(d, 0, 1), new Date(d + 1, 0, 1)); })
    .attr("class", "day")
    .attr("width", cellSize)
    .attr("height", cellSize)
    .attr("x", function(d) { return week(d) * cellSize; })
    .attr("y", function(d) { return day(d) * cellSize; })
    .text(function(d) { return d; });
    .data(function(d) { return d3.time.months(new Date(d, 0, 1), new Date(d + 1, 0, 1)); })
    .attr("class", "month")
    .attr("d", monthPath);

    var csv =[];

What happens here that I can influence?

This controls the size of the rendered calendar. Parameters are passed from the dashboard prompt via presentation variables. If you don’t want users to be able to choose this, simply put static values.

Date format is controlled here. VERY IMPORTANT: you must match the date format in this part of the script to the date format provided within the data set:

means "format = d3.time.format("%Y-%m-%d");"

If your date picture is for example DD.MM.YYYY (e.g. 14.08.2012), then you need to adjust the script to:
format = d3.time.format("%d.%m.%Y ");

Specifies the colour limits (.domain) as retrieved by the dashboard prompts.

Controls the display of the year number in front of the rectangles representing the year:

Leave the rest as-is.



Simply retrieves the values for date and measure from the data set (per row!). Leave this as-is.


  var data = d3.nest()
    .key(function(d) { return d.Date; })
    .rollup(function(d) { return d[0].Metric/100; })

  rect.filter(function(d) { return d in data; })
      .attr("class", function(d) { return "day q" + color(data[d]) + "-9"; })
      .text(function(d) { return d + ": " + percent(data[d]); });

function monthPath(t0) {
  var t1 = new Date(t0.getFullYear(), t0.getMonth() + 1, 0),
      d0 = +day(t0), w0 = +week(t0),
      d1 = +day(t1), w1 = +week(t1);
  return "M" + (w0 + 1) * cellSize + "," + d0 * cellSize
      + "H" + w0 * cellSize + "V" + 7 * cellSize
      + "H" + w1 * cellSize + "V" + (d1 + 1) * cellSize
      + "H" + (w1 + 1) * cellSize + "V" + 0
      + "H" + (w0 + 1) * cellSize + "Z";

What happens here that I can influence?

For the SampleApp example, this transforms the values retrieved from the data set into an index representation for transformation into a percentile representation in the tooltip display.

If you want absolute values, simply change
“.rollup(function(d) { return d[0].Metric/100; })”
“.rollup(function(d) { return d[0].Metric; })”

This colours the date rectangles and the actual tooltip with date information and the added percentile representation of the measure. Here, if you want absolute values, simply change
“.text(function(d) { return d + ": " + percent(data[d]); });”
“.text(function(d) { return d + ": " + data[d] });”

Leave the rest as-is.

So what do you need all-in-all to transplant this into any OBIEE implementation?

1.) The D3 libraries contained in the d3 and d3-cloud folders. Quickest way – if you have the SampleApp lying around – is to just grab them from the analyticsRes folder of the VirtualBox and slap them into your own analyticsRes

2.) An analysis on the date (day!) grain with some measure. Since you can either hard-code the time ranges, size and colour limits, those two are really the bare minimum for this D3 calendar to work.
That’s it. Bob’s your uncle.

UPDATE: Since the D3.js libraries are only dependent of the final browser interpreting the generated code (IE8 will NOT work!), you can transplant this into any version of OBIEE that you fancy. This functionality is NOT tied to OBIEE