Oracle Analytics Server 5.5 Available

Oracle have now released the first version Oracle Analytics Server (OAS), 5.5.  This is essentially the next version of OBIEE, but it is now functionally in-line with Oracle Analytics Cloud (OAC).  Apart from a small number of cloud-only features, such as the Day by Day mobile app and natural language generation, OAS and OAC are basically the same product.

There will be no new releases of OBIEE. All OBIEE functionality is in OAS, along with new features introduced in OAC.

Note at present OAS is only available for Linux x64, other platforms are not available yet.

Also, the repository database must be Oracle, you cannot use the RCU to create your repositories in any other database type – SQL Server, MySQL etc.  Oracle DB versions 11.2 thru 19c can be used, although not Autonomous Cloud variants – we couldn’t find a way to get the RCU connection to accept the secure wallets required for these.

Oracle’s stance is that OAC will still get new features first, with OAS being updated less frequently, perhaps once or twice a year. No one knows what the impact will be of the future version differences between OAC and OAS, but right now (Feb 2020), all content – catalog, RPD, security, etc, can be moved between the two.

In the last few days we’ve taken a bar file snapshot from a production OAC and successfully imported it into OAS – the only additional task required was to import into OAS the secure wallet file for our Autonomous Data Warehouse connection.

The following two URLs take you to the documentation and download sites for OAS:

https://docs.oracle.com/en/middleware/bi/analytics-server/

https://www.oracle.com/solutions/business-analytics/analytics-server/analytics-server.html

Installation is very similar to an OBIEE 12c installation – anyone who has installed OBIEE 12c will recognize most of the steps – java JDK, Fusion Middleware, OAS binaries, RCU and finally OAS configuration.

There are some minor differences – such as a required patch if migrating from OBIEE to OAS – this is included on the download page. Also, the Essbase and Real-Time Decisions options have been removed and are no longer part of the OAS/OAC product.

There are a few points to note about the download page, especially for those not familiar with OBIEE 12c.

 

The five components required are listed, however:

The Java developers Kit link takes you do the general JDK version 8 download page, from here you need to download the correct version for your environment, ideally the most up to date version, which is not 8u191 as mentioned above. At time of writing it’s 8u241

The documentation tab will take you to instructions for installing your java file if you’re unsure.

The link to download ‘Oracle Weblogic Server 12c (12.2.1.4) Generic’ takes you to a download page with a number of options, the page above does mention which one you need, just the bottom link for ‘Fusion Middleware Infrastructure Installer’, ignore the other three links on this page.

The other three download links for Patch 30657796, Oracle Analytic Server and the BI Client are all straight download links.

The five files you will download, along with their sizes are:

jdk-8u241-linux-x64.tar.gz                                   190 MB

fmw_12.2.1.4.0_infrastructure_Disk1_1of1.zip    1.5 GB

p30657796_122140_Generic.zip                            64 KB

Oracle_Analytics_Server_5.5.0.jar                        3.7 GB

OAS-5.5.0-bi_client-win64.zip                              1.5 GB

Enjoy!

OAC/Essbase: Installing the Cube Designer Extension in Smartview.

** This is a blog I originally posted on the RedStack blog site in Jan-18. This blog site has now been taken down, so I've re-posted it here. **

Here’s a quick step-by-step guide to installing the Essbase Cube Designer in Excel from an Oracle Analytics Cloud Essbase service.

If you already have an old version of Smartview installed you must replace it with the latest version from technet  (http://www.oracle.com/technetwork/middleware/epm/downloads/smart-view-1112x-2412371.html)

I had an earlier 11.1.2.6x version but with this the ‘Check for Updates, New Installs and Uninstalls’ in the Extension screen just timed out and froze Excel, not at all helpful!

I’ve now got version 11.1.2.5.720 installed.

Open Excel with a new workbook. From the SmartView ribbon click on the Options icon:

Then click on the Extensions screen:

In here click the ‘Check for Updates, New Installs and Uninstalls’ link

The next screen asks for the location to look for Extension updates.  The number of options here will vary, but you need to locate your Essbase Cloud Service, which in my case is the last location listed here. 

This does of course mean you must have connected to your Essbase Cloud Service at least once using the normal connection panel for SmartView to be aware of it. If you have not done that, then close this window and do that before re-trying.

So, select your Essbase location and click Get Updates.

You will then get the standard login screen to connect to your Essbase cloud service. Enter your details and sign-in.

The previous screen will then update. Reporting that the Extension list has been updated:

Close this window to return to the Extension list screen, which will now have the Cube Designer listed. Click on the Install icon against it:

Confirm you want to apply the extension update:

The extension is then download and installed, it takes only a few seconds. Afterwards shutdown and restart Excel.

You’ll then have a new Ribbon for Cube Designer:

Pretty simple really, just wish the Oracle documentation was a little clearer!

Enjoy!

Using OBIEE with Google BigQuery

It is possible to connect Oracle OBIEE BI reporting tool set to a Google BigQuery dataset for analysis and dashboard reporting by using an ODBC driver provided by Oracle. it's a little more complex than your average data source, so settle down for a long read and enjoy!

Obtaining BigQuery Project details

Google BigQuery can simply be accessed at https://bigquery.cloud.google.com/, there are options to create a new account and load data quickly – I’ve setup a free 365-day trial. Alternatively, if your organisation is already using BigQuery your administrator should be able to help set you up an account and obtain the details below.

For this blog I’ve created a simple dataset by uploading a single CSV file, SALESDATA and creating a small set of additional tables to format it into a dimensional model:

Before considering accessing via OBIEE, there are some items to take note of here. Data is stored in Tables (or views). These are stored with a Dataset, which in turn is stored in a Project.

The fields on a table are known as the Schema.

So, to translate into standard database terms:

Schema = Table fields

Table = Tables

DataSet = Schema

Project = Database

A Project has a name and an ID. The name is displayed on the screen, but the ID is required for connections.

The easiest way to find the Project ID is the click on the little drop-down icon after the Project name and select ‘Switch to Project’ – this will display all projects, including the currently selected one:

So, the Project ID in this case is stately-equinox-206409 (this is auto-assigned by BigQuery, not something I made up!)

To configure an automated driver to connect to BigQuery we need to setup a service account and its security.

To do this you need to access the settings screen. To do this click on the Project drop-down icon and select ‘Switch to project’ then ‘Manage projects…’

In the manage resources screen you will need to check the Organisation is set (my organisation is e-edba.com in this screen shot), this will then display your projects. Click on the Project name to select it.

You can then see all the users who have access to this project. In this case just my demo account:

We don’t want to use this account for automated connections as it won’t be secure and of course my password will change occasionally. Instead we create service account. Click on the ‘Service accounts’ link on the left-hand side.

Click the ‘Create Service Account’ link at the top.

In the Create Service Account screen fill out the fields as follows:

Service Account Name – enter a suitable name. I’ve entered OBIEEConnection.

The service account name automatically gets set to the same name (in lower case with spaces replaced with hyphens). You can change this if you with. It also gets the email address domain prefixed as @projectid.iam.gserviceaccount.com, in my case this is obieeconnection@stately-equinox-206409.iam.gserviceaccount.com.

You then need to pick two roles for the account. Click on the role field to open up a drop-down box. Click on ‘BigQuery’ in the left-hand list then on ‘BigQuery Data Viewer’ in the right-hand list.

Then click ‘add another role’ and select ‘BigQuery User’.

Next tick the ‘Furnish a new private key’ check box. The private key file will be used in place of a password in the ODBC configuration files.   You can select either the default JSON format or the older P12 format.

Ignore the ‘Enable G Suite Domain-wide Delegation’ unless your organisation has wider google suite configuration. In which case speak to your Google administration about this.

Finally click Save.

You should then get a download dialog window for the P12 key file. Save the file in a suitable directory on the pc/server where you will run the BI Administration tool from. It will need to be copied to the OBIEE server later as well.

If you chose a JSON format private key file you will get the following message:

For a P12 private key file you will get the following screen. Note the password that has been set for the P12 private key file. This always seems to default to ‘notasecret’.

The account then appears in the service accounts screen:

This account also appears in the IAM user screen from where you can adjust the roles if required:

The connection from OBIEE will be via ODBC and for this we need some ODBC drivers. These are provided free of charge by Google and can be downloaded from the following URL:

https://cloud.google.com/bigquery/partners/simba-drivers/

Download the appropriate drivers for your OBIEE environment. I needed the Linux 64 bit driver for the VM running my OBIEE service, however the Windows driver is also required as the BI Administration tool needs to connect to BigQuery to import the table objects and this is course only runs under windows.

Configuring the BI Administration Tool

Lets looks at the windows driver and connect via the BI Administration tool first.

The download is a single MSI file called something like SimbaODBCDriverforGoogleBigQuery64_2.1.11.1011.msi

Run this file to start the installation.  You’ll probably get the usual windows warnings about running an unrecognized app, along the lines of this below, you will need to approve it’s running.

Then follow through the installation screens:

Once finished the Samba driver should appear in the ODBC Data Source Admin drivers tab:

We can now configure a data source. Click on the System DSN tab, click Add, then select the new Simba ODBC Driver for Google BigQuery driver:

Then fill out the DSN Setup screen as follows:

Data Source Name – enter a suitable name. Note If OBIEE is running under Linux this must not include spaces. Whilst spaces will work under Windows, we will need to create an identical data source on the Linux server too.

Description – optionally enter a description.

The OAuth Mechanism must be set to ‘Service Authentication’

Leave the User Authentication fields blank.

Under Service Authentication enter the service account email address created in BigQuery earlier on, in my case obieeconnection@stately-equinox-206409.iam.gserviceaccount.com

Now use browse to locate the private key file you downloaded – either JSON or P12.

The ODBC driver comes with its own cacerts.pem certificate file which will be used by default, so leave the ‘Use System Trust Store’ check nox unticked unless you have specific certificates to use.

Lastly you need to choose the Project and Dataset. Both of these are drop-down picklists which if the settings above have been entered correctly will contact BigQuery and automatically provide the names of Project and Dataset.

Finally click Test and, if successful, close the setup screen.

Now we can open the BI Administration Tool.

For the record I’m using version 12.2.1.2.0 of the tool. I’m using a fresh install of OBIEE, so my repository only contains the default Sample App Lite content.

Right click in the Physical layer and select ‘New Database’ from the drop-down menu.

Enter a name for the database and set the Database type to ODBC Basic.

Now click on the Features tab, there is one setting here we need to change for BigQuery, this is the IDENTIFIER_QUOTE_CHAR feature, which defaults to a double quote mark. This means OBIEE automatically puts double quotes around all table and field names in SQL statements. BigQuery does not accept this, so it needs to be removed. Blank out the double quote mark from the Value field:

Click Ok to save the database.

Now right click on the new database and select ‘New Object’ -> ‘Connection Pool…’

Enter a name for the pool – I use the name of the Project in BigQuery.

Set the Call interface to ‘ODBC 3.5’

Drop the Data Source name drop-down choose the ODBC data source created earlier.

Untick the ‘Shared Login’ check box.

Leave all other settings at their default values for now. Click OK to save.

Now right click on the new Connection Pool and select ‘Import Metadata’:

Next choose what to import. There are only Tables and Views in BigQuery.

it will then connect to the Project in BigQuery and bring back all data sets and tables/views within. Select what you need and use the > & >> icons to add them to the repository:

The physical layer should then contain all of the selected tables & views:

This all looks good, however there is a problem which will prevent BigQuery from recognizing the tables in a SQL statement, this is that BigQuery expects the table names to be prefixed with the DataSet name.  OBIEE will not do that automatically, it will simply use the tables names ‘as is’, so for example a simple query on employee_name from the dim_employee table will send the following select:

Select employee_name from dim_employee

However, BigQuery will reject this, the table needs to be prefixed with the dataset:

Select employee_name from PaulsSalesData.dim_employee

The only way to achieve this is to manually add the dataset to the name of each table. Double click on the first table to edit its properties:

And add the dataset name and a period to the name:

Repeat this for all tables:

You will now need to complete the setup of the repository for this data source as you would any other data source. In the physical layer add any joins between the tables – BigQuery does not contain keys that would have allowed the import wizard to detect these automatically.

Then drag the physical schema into the Business Layer, enable it and add any addition content (dimensions hierarchies, custom calcs etc). Also do not forget to set the aggregation type for any numeric fields (sum). Then drag that into the presentation layer:

Now save the repository, checking the consistency as you go. All will always get one warning message about the features of our database in the physical layer not matching the defaults – this is caused by the removal of the double-quote marks against the IDENTIFIER_QUOTE_CHAR feature – so this can be ignored.

Configuring OBIEE

Before we can login to OBIEE and try to run a report, we need to configure the ODBC driver on the OBIEE server as well.  OBIEE will use the data source name specified in the repository connection pool, so once the drivers are installed we need to create an identically named data source.

My OBIEE is running on a Linux VM. To install the ODBC driver downloaded earlier the file, SimbaODBCDriverforGoogleBigQuery64_2.1.11.1011.tar.gz, needs to be FTP’d to the server and either under the root user unpack with the following command:

tar --directory=/opt -zxvf SimbaODBCDriverforGoogleBigQuery64_2.1.11.1011.tar.gz

You then need to edit the simba.googlebigqueryodbc.ini to configure a few settings.

vi /opt/simba/googlebigqueryodbc/lib/64/simba.googlebigqueryodbc.ini

the original file contains:

Firstly, the DriverManagerEncoding needs changing to UTF-8.

the [DataDirect][ODBC lib] Unicode converter truncated character errors if left at UTF-32.

ErrorMessagesPath needs the $(INSTALLDIR) replacing with the actual directory, in my case /opt/simba/googlebigqueryodbc/ErrorMessages

LogLevel can be left at 0, which is no logging or increased. I’ve set mine to 4, which is general information

LogPath need setting to appropriate directory

Also, LogCount can be added to restrict the number of log files to keep.

So, my ini file looks like this:

There is a PDF document explaining all the configuration settings here:

/opt/simba/googlebigqueryodbc/Simba ODBC Driver for Google BigQuery Install and Configuration Guide.pdf

Next the BigQuery service account private key file downloaded earlier needs to be FTP’d up to the server. You can place this anywhere as it will be referred to via its full path. Make sure to upload this under the user that Oracle runs under, not root, otherwise OBIEE may not have access to it.

I’ve put mine in a new directory /u01/BigQueryDriver/ along with the ODBC driver installer run earlier.

Now we can setup our ODBC data source. This needs to be done OBIEEs odbc.ini file located under <obiee_home>/user_projects/domains/bi/config/fmwconfig/bienv/core/odbc.ini

Edit this file, for example with vi, in my case:

vi /u01/app/obiee12214/user_projects/domains/bi/config/fmwconfig/bienv/core/odbc.ini

First under the [ODBC Data Sources] section add a new record for our data source using the same name as above when creating the ODBC data source under windows for the BI Administration Tool. In my case I’ve added the line:

BigQuery_PaulsSalesData=Simba ODBC Driver for Google BigQuery

Then below create a new section titled the data source name “[BigQuery_PaulsSalesData]” with the following settings:

Driver=/opt/simba/googlebigqueryodbc/lib/64/libgooglebigqueryodbc_sb64.so

This must point to the location of the libgooglebigqueryodbc_sb64.so file installed with the simba driver. It’s probably under /opt/simba/googlebigqueryodbc/lib/64, but check first.

Catalog=stately-equinox-206409

               This is the Project ID from BigQuery

OAuthMechanism=0

               This sets the authentication method to use service accounts.

Email=obieeconnection@stately-equinox-206409.iam.gserviceaccount.com

               This is the email address of our service account

KeyFilePath=/u01/BigQueryDriver/stately-equinox-206409-3e3df8089ed6.json

               This is the full path to our private key file for the service account

SQLDialect=1

The SQLDialect must set to 1, which indicates modern standard SQL. The default is 0 which would be legacy SQL which would not work.

LogLevel=4

               Logging level, same as the odbc driver ini file above

LogPath=/u01/simba_logs

               Log file path, same as the odbc driver ini file above

LogFileCount=10

Log File Count, same as the odbc driver ini file above

LogFileSize=200

               Maximum size of the log files.

The last four log settings you can set to your own preference.

So, my odbc ini file looks like this:

We can now perform a test of this using the OBIEE nqcmd.sh (nqcmd.bat on windows) command.

First change to the directory for this command:

cd <oracle_home>/user_projects/domains/bi/bitools/bin

or in my case:

cd /u01/app/obiee12214/user_projects/domains/bi/bitools/bin

now create a text file called bigquery.sql and insert a simple select, for example:

select sum(REVENUE) from PaulsSalesData.SALESDATA

then run the following command:

./nqcmd.sh -d BigQuery_PaulsSalesData -u weblogic -p Password1 -s bigquery.sql -o bigquery.txt

This parameters are as follows:

               -d           this is the odbc data source name

               -u           this is a user in OBIEE, I’m using the weblogic admin user

               -p           the password for this user

               -s            the name of the SQL file created above

               -o           the name of a text file to output the results to.

When you run this, you should find that the output file contains the select statement (which it displays twice for some reason) and the results returned from BigQuery:

If you see any errors here then something has gone wrong either with the connection to BigQuery, the ODBC data source settings, or possibly even your SQL (try running this directly in the BigQuery web site to check it’s ok)

I came across three errors when I first ran this:

“[Simba][BigQuery] (100) Error interacting with REST API: Peer certificate cannot be authenticated with given CA certificates

Connect open failed”

There could be many reasons why a certificate could not be authenticated. The best option is to open a browser on the server (I already had firefox installed on my linux server) and connect to the BigQuery cloud web site. This should show any certificate problems and, hopefully, the reason. In my case the certificate error stated that the current certificate in the web site wasn’t valid a until a certain date.

I hadn’t noticed before, but the date on my linux VM wasn’t current and was before the valid date of the certificate, so I manually reset it:

date -s "26 JUN 2018 14:50:00"

This led to the second error:

[Simba][BigQuery] (80) Authentication failed: invalid_grant

It turns out that manually setting the date/time isn’t good enough, the time sync between your server and the BigQuery server must be very accurate. I decided to use the linux NTP package to sync properly – I can’t do into how to do that here, but your linux admin guys should be able to help, or just google it!

/usr/sbin/ntpdate pool.ntp.org

The last error I had was a simple permissions issue in BigQuery, I hadn’t give the user both roles mentioned earlier on:

[Simba][BigQuery] (100) Error interacting with REST API: Access Denied: Project stately-equinox-206409: The user obieeconnection@stately-equinox-206409.iam.gserviceaccount.com does not have bigquery.jobs.create permission in project stately-equinox-206409.

Statement preparation failed

Once your test query is running correctly you are now ready to login to OBIEE and start creating reports!

Here I’ve created a new analysis on my PaulsSalesData subject area. Note that the tables do not contain the PaulsSalesData. Prefix as I removed them from the presentation layer, it’s only the database layer they are required in.

And this can be displayed any way I want:

If report is running (i.e not erroring) but not bring back any data or the data does not match what you expect, you can extract the SQL OBIEE has built and run it directly in BigQuery. In OBIEE go to the Administration tab (you’ll need to be logged in under an account with Administrator privileges) then click the ‘Manage Sessions’ link:

This displays all session details for all users, so it could be quite a long list, but towards the bottom you’ll find your query by looking in the ‘user’ field:

The Statement in this screen is meaningless as this is the query the OBIEE front end has sent to the BI Server in the background. We need the SQL this generates to send to BigQuery. Click on the ‘View log’ link in the Action column.

This displays a lot of information about the BI server query, however towards the bottom you’ll find the ‘standard’ SQL select statement sent to BigQuery. Copy this and login to BigQuery.

Create a new Query in BigQuery, paste in the select command and run it to see the results:

If you get no data, or incorrect data, you can investigate it here in BigQuery and if necessary alter the database details in the BI Administration tool to accommodate your findings.

If you get an error along the lines of:

Then it’s probably because your BigQuery session is set to use legacy SQL.

Click the ‘Show Options’ button and untick the ‘Use Legacy SQL’ option then run the query again.

That’s it! Your now ready to build your reports and dashboards in OBIEE on your BigQuery data.

However that may not be the end of the story, given the simplistic structure of BigQuery datasets and the charging method of ‘pay per query & quantity’ you may want to investigate ways of manipulating the data in BigQuery (via views and summary tables) and fine tune the caching options in OBIEE to minimize the data extracted from BigQuery, especially if you have lots of analyses on dashboards frequently viewed by many users.

Enjoy!