Google BigQuery Example - Native Query (ServerSide): Query with CAST unix TIMESTAMP datatype column as datetime
This example shows how to query timestamp column as DateTime. E.g. 73833719.524272 should be displayed as 1972-05-04 or with milliseconds 1972-05-04 1:21:59.524 PM then use CAST function (you must use #DirectSQL prefix)
The ZappySys API Driver is a user-friendly interface designed to facilitate the seamless integration of various applications with the Google BigQuery API. With its intuitive design and robust functionality, the ZappySys API Driver simplifies the process of configuring specific API endpoints to efficiently read or write data from Google BigQuery.
Following examples shows how to Native Query (ServerSide): Query with CAST unix TIMESTAMP datatype column as datetime from Google BigQuery using ZappySys API Driver. You can explore additional examples for the Azure DevOps Connector here.
#DirectSQL
SELECT id, col_timestamp, CAST(col_timestamp as DATE) AS timestamp_as_date, CAST(col_timestamp as DATETIME) AS timestamp_as_datetime
FROM MyProject.MyDataset.MyTable
LIMIT 10Microsoft SQL Server OPENQUERY Query - Google BigQuery Example
Following examples shows how to Native Query (ServerSide): Query with CAST unix TIMESTAMP datatype column as datetime in Microsoft SQL Server using OPENQUERY Query. This command facilitates the execution of pass-through queries on remote servers. Below example is demonstrating the usage of OPENQUERY.
SELECT * FROM OPENQUERY([MY_LINKED_SERVER_NAME],
'#DirectSQL
SELECT id, col_timestamp, CAST(col_timestamp as DATE) AS timestamp_as_date, CAST(col_timestamp as DATETIME) AS timestamp_as_datetime
FROM MyProject.MyDataset.MyTable
LIMIT 10');Microsoft SQL Server EXEC Query - Google BigQuery Example (Handling larger SQL text)
The major drawback of OPENQUERY is its inability to incorporate variables within SQL statements, which often leads to the use of cumbersome dynamic SQL (with numerous ticks and escape characters).
Fortunately, there is a solution. Starting with SQL 2005 and onwards, you can utilize the EXEC (your_sql) AT your_linked_server syntax. Following examples shows how to Native Query (ServerSide): Query with CAST unix TIMESTAMP datatype column as datetime in Microsoft SQL Server using EXEC Query.
DECLARE @MyQyery NVARCHAR(MAX) = '#DirectSQL
SELECT id, col_timestamp, CAST(col_timestamp as DATE) AS timestamp_as_date, CAST(col_timestamp as DATETIME) AS timestamp_as_datetime
FROM MyProject.MyDataset.MyTable
LIMIT 10';
EXE (@MyQyery) AT [MY_LINKED_SERVER_NAME];
Getting Started with Examples
ZappySys API Driver is a powerful software solution designed to facilitate the extraction and integration of data from a wide range of sources through APIs. Its intuitive design and extensive feature set make it an essential asset for any organization dealing with complex data integration tasks.
To get started with examples using ZappySys API Driver, please click on the following applications:
Key features of the ZappySys API Driver include:
The API ODBC driver facilitates the reading and writing of data from numerous popular online services (refer to the complete list here) using familiar SQL language without learning complexity of REST API calls. The driver allows querying nested structure and output as a flat table. You can also create your own ODBC / Data Gateway API connector file and use it with this driver.
Intuitive Configuration: The interface is designed to be user-friendly, enabling users to easily set up the specific API endpoints within Google BigQuery without requiring extensive technical expertise or programming knowledge.
Customizable Endpoint Setup: Users can conveniently configure the API endpoint settings, including the HTTP request method, endpoint URL, and any necessary parameters, to precisely target the desired data within Google BigQuery.
Data Manipulation Capabilities: The ZappySys API Driver allows for seamless data retrieval and writing, enabling users to fetch data from Google BigQuery and perform various data manipulation operations as needed, all through an intuitive and straightforward interface.
Secure Authentication Integration: The driver provides secure authentication integration, allowing users to securely connect to the Google BigQuery API by inputting the necessary authentication credentials, such as API tokens or other authentication keys.
Error Handling Support: The interface is equipped with comprehensive error handling support, ensuring that any errors or exceptions encountered during the data retrieval or writing process are efficiently managed and appropriately communicated to users for prompt resolution.
Data Visualization and Reporting: The ZappySys API Driver facilitates the seamless processing and presentation of the retrieved data from Google BigQuery, enabling users to generate comprehensive reports and visualizations for further analysis and decision-making purposes.
Overall, the ZappySys API Driver serves as a powerful tool for streamlining the integration of applications with Google BigQuery, providing users with a convenient and efficient way to access and manage data, all through a user-friendly and intuitive interface.