Hive 4 Auth with standalone JAR download, numbered Auth Notes, extra SQL examples. Initial version. Connect to HiveServer2 with the standalone JDBC JAR. JDBC Bridge then exposes Hive SQL to Power BI, SQL Server Linked Server via ZappySys Data Gateway, Crystal Reports, SSRS, Azure Data Factory, and other ODBC tools.

1. Note the HiveServer2 host and binary port (default 10000) and the default database name.
2. Create a Hive / LDAP user if the cluster requires authentication. Lab clusters sometimes allow empty user and password.
3. Replace hive-instance-host-name and the database in the JDBC URL after Finish (the wizard hides the URL; edit it on the DSN Main UI).
4. Prefer the standalone JAR the wizard downloads. Do not mix it with a partial Hadoop classpath.
5. Finish the wizard. Then click Test Connection on the DSN Main UI (the wizard does not run Test Connection).
6. Done. You can query from C#, Python, PowerShell, and ODBC apps.

]]> Hive 4 HiveServer2 with SSL and user/password (LDAP or custom). Power BI's old Hive LLAP ODBC path is being deprecated; this JDBC standalone JAR is the durable Excel / SSIS / Linked Server path.

1. Confirm Hive 4.x HiveServer2 host, port 10000 (or your HS2 port), and that SSL is enabled.
2. Create or reuse an LDAP / Hive user. Paste user and password here. Do not use a personal employee login for unattended refresh.
3. The wizard downloads hive-jdbc-4.2.0-standalone.jar. Keep SSL=true unless your lab is plaintext (then use Default Auth).
4. After Finish, edit the JDBC URL on the DSN Main UI to replace the host (e.g. MyHostName) and database (e.g. MyDatabase).
5. Finish the wizard. Then click Test Connection on the DSN Main UI (the wizard does not run Test Connection).
6. Done. You can query from C#, Python, PowerShell, and ODBC apps.

]]> Lists tables in the current Hive database. Use this in Power BI or a SQL Server Linked Server to confirm the catalog.

]]> Returns selected columns for employees in the Sales department. Use WHERE department = 'Sales' to filter by department. Works in Excel, SSRS, and Crystal Reports.

]]> Joins employees to departments. Typical Azure Data Factory or SSIS extract.

]]> Aggregates salary per department. Use in Power BI before a visual.

]]> = 1]]> Returns the top 100 rows by salary. Useful as a preview in Crystal Reports or Excel.

]]> Ranks employees by salary within each department (highest first). The result includes a salary rank per department.

]]> Extracts the city field from a JSON string in the user_data column. The column should contain JSON with an address and city (e.g. nested under address).

]]> Turns array elements into separate rows and filters for users interested in hiking. Assumes a table with an array column for interests.

]]> Parses the browser name (e.g. Firefox, Chrome, Safari, MSIE) from the user_agent string. For large tables, you can limit the number of rows returned.

]]> Returns the number of employee rows. Use from Linked Server or ADF to sanity-check volume.

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