Coding

To select columns based on their names in Oracle, you can specify the column names in the SELECT statement separated by commas. Make sure to use the specific column names that you want to retrieve data from, following the SELECT keyword. This will allow you to fetch only the specific columns you are interested in without retrieving unnecessary data.

To convert a Unix timestamp to a local date in Oracle, you can use the TO_DATE function along with the TIMESTAMP data type. First, you need to convert the Unix timestamp to a TIMESTAMP data type using the TO_TIMESTAMP function. This will give you a timestamp value that represents the Unix timestamp in Oracle. Then, you can use the TO_DATE function to convert this timestamp to a local date format based on your desired format mask.

To check if all values in a column are the same in Oracle, you can use a query with the GROUP BY clause. This query groups the rows by the column you want to check and then counts the distinct values in that column. If the count is equal to 1, then all values in the column are the same. The query would look something like this:SELECT COUNT(DISTINCT column_name) as cnt FROM table_name GROUP BY column_name;If the resulting count is 1, then all values in that column are the same.

To create a table in Oracle, you can use the CREATE TABLE statement followed by the table name and columns with their data types and constraints. Here is a basic syntax example:CREATE TABLE table_name ( column1 datatype [constraint], column2 datatype [constraint], ... );You can define as many columns as needed in the table, along with constraints like NOT NULL, PRIMARY KEY, FOREIGN KEY, UNIQUE, etc.

To connect to an Oracle database from a JSP file, you will need to first include the JDBC driver for Oracle in your project. You can download the driver from the Oracle website and add it to your project's classpath.Next, you will need to establish a connection to the Oracle database using the JDBC API. You can do this by creating a Connection object and passing in the URL of the database, as well as the username and password for authentication.

To find the number of rows present in a JSON array in Oracle, you can use the JSON_TABLE function along with the JSON_ARRAY function. First, you need to convert the JSON array into rows using JSON_TABLE, and then you can use the COUNT function to find the number of rows in the result set. Finally, you can use the SELECT statement to retrieve the count of rows in the JSON array.How can I get the size of a JSON array in Oracle using a query.

To update two tables using a single procedure in Oracle, you can start by creating a stored procedure that includes the UPDATE statements for both tables. Within the procedure, you would write separate UPDATE statements for each table, making sure to include the necessary conditions and set values for the updates.The procedure can take input parameters if needed to pass values for the updates. Once the procedure is created, you can execute it to update both tables simultaneously.

To multiply rows in an Oracle query by a count column, you can use the COUNT function along with a mathematical operator such as multiplication (*) in your SELECT statement. First, you need to retrieve the count column for each row using the COUNT function. Then, you can multiply the other columns in the row by the value in the count column using the multiplication operator. This will result in the multiplication of each row in the query by its corresponding count column value.

To get the year and month in number form in Oracle, you can use the EXTRACT function with the 'year' and 'month' options. This function allows you to extract the year and month components from a date field and return them as numbers.

To set all rows for a materialized view in Oracle, you can use the "REFRESH FORCE ON DEMAND WITH ROWID" command. This command will refresh all rows in the materialized view by re-executing the query that was used to create the view. Additionally, you can also set the "START WITH" and "NEXT" options to schedule regular refreshes of the materialized view to ensure that all rows are up to date.