Connection Tool - Programmatically Remove Unused Datasource Connections, and List All Connections
Managing connections within your Sisense environment can become complex over time, if there are a large number of connections, and connections are often added, and replace earlier datasource connections. In some scenarios unused connections can accumulate, potentially cluttering the connection manager UI with no longer relevant connections. Although unused connections typically represent minimal direct security risk, it's considered best practice to maintain a clean, organized list of connections, and in some scenarios it can be desired to remove all unused connections. Sisense prevents the deletion of connections actively used in datasources, safeguarding your dashboards and datasources from disruptions. However, inactive or "orphaned" connections remain after datasources are deleted or a connection is replaced, potentially contributing to unnecessary UI complexity in the connection manager UI. Connections can be of any type Sisense supports, common types include various SQL connections, Excel files, and CSV files, as well as many data providers, such as Big Panda. This tool can also be used to list all connections, with no automatic deletion of unused connections.
Coinbase Data Connector
Download: Coinbase Connector Introduction: This article will explain how to make a REST API connection to Coinbase's API Purpose/Benefits: This connector gives you the ability to pull in data about cryptocurrencies from Coinbase into your Sisense ElastiCube How to Install and Configure the Coinbase Connector: Step 1: Download the Connector and unzip the contents into your C:\Program Files\Sisense\DataConnectors\DotNetContainer\Connectors folder. *You may need to move your Rest dll file into the connector (replace the current one) - you can do this by going to C:\Program Files\Sisense\DataConnectors\DotNetContainer\Rest and copying the .dll to the Coinbase Connector Step 2: Restart the Sisense.Discovery and Sisense.CLRConnectorsContainer services on the Sisense machine Step 3: The driver has tables already configured for BTC, ETH and LTC You can add/remove depending what would you like to track: Step 4: Open the ElastiCube Manager, create a new ElastiCube and select the Coinbase Connector. Reference/Notes: Coinbase Website API Documentation
Resolving Missing Generic JDBC Connector in Sisense
This article addresses the issue where the Generic JDBC connector is not visible under available connectors for users logged in with a designer account in Sisense version 2023.6 or newer. This problem arises due to changes in the framework that affect the visibility of certain connectors for non-admin userResolving DBLink Issues in Sisense for Postgres Connections
This article addresses the issue of using DBLink with Postgres connections in Sisense. DBLink is a feature in PostgreSQL that allows users to connect and query data across different databases. However, users may encounter limitations when attempting to use DBLink within Sisense's custom import queries. This guide explains the issue and offers a solution to effectively manage data from multiple databases in Sisense.Resolving Missing Generic JDBC Connector in Sisense
This article addresses the issue where the Generic JDBC connector is not visible under available connectors for users logged in with a designer account in Sisense version 2023.6 or newer. This problem arises due to changes in the framework that affect the visibility of certain connectors for non-admin users.How to record a .har file and identify if specific requests are present in logs
To record a .har file in Chrome, open Developer Tools > Network tab, enable recording, clear logs, and reproduce the issue before exporting the file. To check for jaql requests, filter by "jaql" in the Network tab and inspect the request status and X-Request-ID. For on-premise Sisense, use cat /var/log/sisense/sisense/<log_file_name> | grep <X-Request-ID> (single-node) or kubectl exec (multi-node) to search logs for the request.Resolving MongoDB Connector Performance Issues in Sisense
Resolving MongoDB Connector Performance Issues in Sisense Summary This article addresses performance issues caused by the MongoDB connector in Sisense, specifically related to the addition of an unnecessary parameter in queries and as a result, leads to inefficient query execution and overall system performance degradation. The article provides steps to resolve the issue and improve performance. Main Content Issue Description The MongoDB connector in Sisense may add an unnecessary parameter {"$not": {"$type": 2}} to queries translated from SQL to MQL. This additional parameter prevents the use of indexes in the execution plan, resulting in full table scans and significantly increased query times. This issue affects the initialization step of the EC build, causing delays in Cube builds and overall system performance failures. Steps to Resolve the Issue Identify the MongoDB Connector Version: Ensure you are using the MongoDB connector version 1.1, which is auto-installed as part of Sisense Fusion. Disable Mixed Type Filter: Use the parameter EnableMixedTypeFilter=0 to remove the additional filter {"$type": 2} from the queries. This can be done by adding the parameter to your MongoDB connector configuration. Verify Query Performance: After applying the parameter, monitor the query performance to ensure that the unnecessary filter is removed and indexes are being used. Use MongoDB Atlas or other monitoring tools to check the "Examined:Returned Ratio" for your queries. Upgrade MongoDB Connector: If the issue persists, consider upgrading the MongoDB connector to a version that supports MongoDB Version 6.0.16. Contact Sisense support to get assistance with the upgrade process. Troubleshooting Tips Check Indexes: Ensure that all required indexes are added to your MongoDB collections. Use MongoDB Atlas or other tools to review and optimize your indexes. Monitor Query Insights: Use MongoDB Atlas - Data Services - View Monitoring - queryInsights - profiler to monitor the performance of your queries. Identify queries with a high "Examined:Returned Ratio" and investigate further. Review Execution Plans: Analyze the execution plans of your queries to ensure that indexes are being used effectively. Look for any additional filters or parameters that may be affecting performance. Check out this related content: Academy Documentation
