{"id":46722,"date":"2022-11-04T00:00:00","date_gmt":"2022-11-04T07:00:00","guid":{"rendered":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/blog\/using-griddb-to-analyze-distances-of-asteroids-to-earth\/"},"modified":"2025-11-13T12:56:14","modified_gmt":"2025-11-13T20:56:14","slug":"using-griddb-to-analyze-distances-of-asteroids-to-earth","status":"publish","type":"post","link":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/en\/blog\/using-griddb-to-analyze-distances-of-asteroids-to-earth\/","title":{"rendered":"Using GridDB to Analyze Distances of Asteroids to Earth"},"content":{"rendered":"

In this article, we will use GridDB to analyse how scientists decide whether or not asteroids are dangerous to Earth, that is, whether or not they will leave their orbit and land here on Earth, potentially harming the population.<\/p>\n

Full source code can be found here: https:\/\/github.com\/griddbnet\/Blogs\/tree\/asteroids_distance<\/a><\/p>\n

Exporting and Importing dataset using GridDB<\/h2>\n

GridDB is a highly scalable and optimized in-memory No SQL database that allows parallel processing for higher performance and efficiency, especially for time-series databases. We will be using GridDB’s node js client, which allows us to connect GridDB to node js and import or export data in real-time.<\/p>\n

These are the columns that are present in our dataset:<\/p>\n

    \n
  1. id : ID given to the asteroids by NASA scientists.<\/li>\n
  2. new_name : Names given to the asteroids by NASA scientists.<\/li>\n
  3. est_diameter_min : The minimum estimated diameter of the asteroids.<\/li>\n
  4. est_diameter_max : The maximum estimated diameter of the asteroids.<\/li>\n
  5. relative_velocity : The relative velocity of the asteroids compared to Earth.<\/li>\n
  6. miss_distance : Asteroids’ distance away from the Earth.<\/li>\n
  7. orbiting_body: Asteroids’ orbital around the specific body.<\/li>\n
  8. sentry_object: Whether the asteroid collided with other body (satellites, etc) in the space.<\/li>\n
  9. absolute_magnitude: The magnitude of force by which they would hit the Earth according to their mass-force ratio.<\/li>\n
  10. hazardous : Are the asteroids at hazardous range? (Outcome Variable)<\/li>\n<\/ol>\n

    To upload the dataset to GridDB, we would read the CSV file that contains the data which is taken from This Kaggle Dataset<\/a><\/p>\n

    Now, we will create a GridDB container to pass our database schema to the GridDB to be able to generate the design of the database before inserting the row information. Next, we would insert our data into the GridDB. We have now successfully exported the dataset to the GridDB platform.<\/p>\n

    On the other hand, to import the dataset from the GridDB platform, we will use TQL, GridDB’s query language similar to SQL. We will create a container and store the fetched data in it. The next step would be to extract the rows in order of the column info and save it into a data frame to use for data visualization and analysis.<\/p>\n

    For the data visualization and analysis, we will be using the following library for NodeJS.<\/p>\n