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Write a Simple Go Application to work with SQL Analysis Services Data on Linux

Use the CData ODBC Driver for SQL Analysis Services and unixODBC to create a simple Go app with live connectivity to SQL Analysis Services data.

Go is an open source programming language that enables you to easily build software on Linux/UNIX machines. When Go is paired with the ODBC Driver for SQL Analysis Services and unixODBC you are able write applications with connectivity to live SQL Analysis Services data. This article will walk you through the process of installing the ODBC Driver for SQL Analysis Services, configuring a connection using the unixODBC Driver Manager, and creating a simple Go application to work with SQL Analysis Services data.

Using the CData ODBC Drivers on a Unix/Linux Machine

The CData ODBC Drivers are supported in various Red Hat-based and Debian-based systems, including Ubuntu, Debian, RHEL, CentOS, and Fedora. There are also several libraries and packages that are required, many of which may be installed by default, depending on your system. For more information on the supported versions of Linux operating systems and the required libraries, please refer to the "Getting Started" section in help documentation (installed and found online).

Installing the Driver Manager

Before installing the driver, you need to be sure that your system has a driver manager. For this article, you will use unixODBC, a free and open source ODBC driver manager that is widely supported.

For Debian-based systems like Ubuntu, you can install unixODBC with the APT package manager:

$ apt-get install unixODBC unixODBC-dev

For systems based on Red Hat Linux, you can install unixODBC with yum or dnf:

$ yum install unixODBC unixODBC-devel

The unixODBC driver manager reads information about drivers from an odbcinst.ini file and about data sources from an odbc.ini file. You can determine the location of the configuration files on your system by entering the following command into a terminal:

$ odbcinst -j

The output of the command will display the locations of the configuration files for ODBC data sources and registered ODBC drivers. User data sources can only be accessed by the user account whose home folder the odbc.ini is located in. System data sources can be accessed by all users. Below is an example of the output of this command:

DRIVERS............: /etc/odbcinst.ini SYSTEM DATA SOURCES: /etc/odbc.ini FILE DATA SOURCES..: /etc/ODBCDataSources USER DATA SOURCES..: /home/myuser/.odbc.ini SQLULEN Size.......: 8 SQLLEN Size........: 8 SQLSETPOSIROW Size.: 8

Installing the Driver

You can download the driver in standard package formats: the Debian .deb package format or the .rpm file format. Once you have downloaded the file, you can install the driver from the terminal.

The driver installer registers the driver with unixODBC and creates a system DSN, which can be used later in any tools or applications that support ODBC connectivity.

For Debian-based systems like Ubuntu, run the following command with sudo or as root: $ dpkg -i /path/to/package.deb

For systems that support .rpms, run the following command with sudo or as root: $ rpm -i /path/to/package.rpm

Once the driver is installed, you can list the registered drivers and defined data sources using the unixODBC driver manager:

List the Registered Driver(s)

$ odbcinst -q -d CData ODBC Driver for SQL Analysis Services ...

List the Defined Data Source(s)

$ odbcinst -q -s CData SSAS Source ...

To use the CData ODBC Driver for SQL Analysis Services with unixODBC, you need to ensure that the driver is configured to use UTF-16. To do so, edit the INI file for the driver (cdata.odbc.ssas.ini), which can be found in the lib folder in the installation location (typically /opt/cdata/cdata-odbc-driver-for-ssas), as follows:

cdata.odbc.ssas.ini

... [Driver] DriverManagerEncoding = UTF-16

Modifying the DSN

When the driver is installed, a system DSN should be predefined. You can modify the DSN by editing the system data sources file (/etc/odbc.ini) and defining the required connection properties. Additionally, you can create user-specific DSNs that will not require root access to modify in $HOME/.odbc.ini.

To connect, provide authentication and set the Url property to a valid SQL Server Analysis Services endpoint. You can connect to SQL Server Analysis Services instances hosted over HTTP with XMLA access. See the Microsoft documentation to configure HTTP access to SQL Server Analysis Services.

To secure connections and authenticate, set the corresponding connection properties, below. The data provider supports the major authentication schemes, including HTTP and Windows, as well as SSL/TLS.

  • HTTP Authentication

    Set AuthScheme to "Basic" or "Digest" and set User and Password. Specify other authentication values in CustomHeaders.

  • Windows (NTLM)

    Set the Windows User and Password and set AuthScheme to "NTLM".

  • Kerberos and Kerberos Delegation

    To authenticate with Kerberos, set AuthScheme to NEGOTIATE. To use Kerberos delegation, set AuthScheme to KERBEROSDELEGATION. If needed, provide the User, Password, and KerberosSPN. By default, the data provider attempts to communicate with the SPN at the specified Url.

  • SSL/TLS:

    By default, the data provider attempts to negotiate SSL/TLS by checking the server's certificate against the system's trusted certificate store. To specify another certificate, see the SSLServerCert property for the available formats.

You can then access any cube as a relational table: When you connect the data provider retrieves SSAS metadata and dynamically updates the table schemas. Instead of retrieving metadata every connection, you can set the CacheLocation property to automatically cache to a simple file-based store.

See the Getting Started section of the CData documentation, under Retrieving Analysis Services Data, to execute SQL-92 queries to the cubes.

/etc/odbc.ini or $HOME/.odbc.ini

[CData SSAS Source] Driver = CData ODBC Driver for SQL Analysis Services Description = My Description User = myuseraccount Password = mypassword URL = http://localhost/OLAP/msmdpump.dll

For specific information on using these configuration files, please refer to the help documentation (installed and found online).

Creating a Simple Go App for SQL Analysis Services Data

With the Driver Manager installed and the DSN configured, you are ready to create a simple Go application to work with your SQL Analysis Services data. To start, install a Go driver for ODBC databases. While there are several options available, this article will use the odbc driver found at https://github.com/alexbrainman/odbc.

Installing odbc on Linux

To install the odbc driver for Go, you will need to first ensure that you define the GOPATH environment variable:

export GOPATH=$HOME/golang/go

Once GOPATH is defined, you are ready to install the Go driver for ODBC databases:

$ go get github.com/alexbrainman/odbc

Now you are ready to create and execute a simple Go application.

Sample Go Application

The sample application issues a simple SQL SELECT query for SQL Analysis Services data and displays the results. Create the directory $GOPATH/src/cdata-odbc-ssas and create a new Go source file, copying the source code from below.

cdata-odbc-ssas.go

package main import ( _ "github.com/alexbrainman/odbc" "database/sql" "log" "fmt" ) func main() { db, err := sql.Open("odbc", "DSN=CData SSAS Source") if err != nil { log.Fatal(err) } var ( fiscal_year string sales_amount string ) rows, err := db.Query("SELECT Fiscal_Year, Sales_Amount FROM Adventure_Works WHERE Fiscal_Year = ?", "FY 2008") if err != nil { log.Fatal(err) } defer rows.Close() for rows.Next() { err := rows.Scan(&fiscal_year, &sales_amount) if err != nil { log.Fatal(err) } fmt.Println(fiscal_year, sales_amount) } err = rows.Err() if err != nil { log.Fatal(err) } defer db.Close() }

In the terminal, navigate to the Go application directory and build the application:

$ go build

After the application builds, you will be able to execute the application, displaying your SQL Analysis Services data:

$ ./cdata-odbc-ssas

At this point, you have a simple Go application for working with SQL Analysis Services data. From here, you can easily expand the application, adding deeper read/write functionality through familiar SQL queries.