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4 min readIn PostgreSQL, the objects in the database are stored in the system table called user_objects. This table contains information about all the objects created by users, such as tables, indexes, sequences, etc.The column temporary in the user_objects table indicates whether the object is temporary or not. A temporary object is created for a specific session and is automatically dropped at the end of the session.
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6 min readWhen dealing with multiple queries in PostgreSQL, it is important to understand the concept of transaction management. By using transactions, you can group multiple queries together and ensure that they are processed as a single unit of work.One common approach to handling multiple queries is to use the BEGIN, COMMIT, and ROLLBACK statements to start, commit, and rollback transactions.
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3 min readTo use a trained model in TensorFlow Serving, you first need to export your trained model in the SavedModel format. This can be done using the tf.saved_model.save() function in TensorFlow.Once you have exported your model, you can start the TensorFlow Serving server and load your model into it using the --model_base_path flag to specify the directory where your SavedModel is stored.
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5 min readTo create custom sequences in PostgreSQL, you can use the CREATE SEQUENCE statement followed by the sequence name and any additional options you want to specify. You can set starting values, increment values, and maximum or minimum values for the sequence.
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5 min readTo convert a JSON object to a table in PostgreSQL, you can use the json_to_recordset function along with a common table expression (CTE). First, you can use the json_to_recordset function to extract the JSON data into individual rows and columns. Then, you can use the CTE to create a temporary table from the extracted data. Finally, you can insert the data from the temporary table into the target table using an INSERT INTO statement.
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6 min readTo enable GPU support in TensorFlow, you need to make sure that you have installed the GPU version of TensorFlow. This can be done by installing the TensorFlow-GPU package using pip. Additionally, you will need to have CUDA and cuDNN installed on your system. Once you have all the necessary requirements in place, TensorFlow will automatically use the GPU for computations. You can verify that GPU support is enabled by checking the list of available devices in TensorFlow using the command tf.
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4 min readTo log a "new table" from an update trigger in PostgreSQL, you can create a trigger function that captures the new values of the table being updated and logs it into another table. Within the trigger function, you can access the NEW record, which contains the new values of the row being updated. By inserting these values into a separate logging table within the trigger function, you can effectively log the "new table" for auditing or tracking purposes.
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5 min readTo create an auto-increment column in PostgreSQL, you need to use the SERIAL data type when defining the column in your table. This data type creates an auto-incrementing integer column that automatically generates unique values for new rows inserted into the table.
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6 min readIn PostgreSQL, you can achieve returning multiple where clauses in different rows by using the UNION ALL operator.You can construct separate SELECT statements with different WHERE clauses and then use UNION ALL to combine the results into a single result set. Each SELECT statement will return rows that match the respective WHERE clause, and the UNION ALL operator will concatenate these results.
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8 min readTo record the results from TensorFlow to a CSV file, you can follow these steps:First, you need to define the data that you want to record as a TensorFlow variable or tensor.Next, create a TensorFlow session and run the desired operation to get the results.Once you have the results, convert them to a format that can be saved in a CSV file, such as a NumPy array.Use Python libraries like NumPy or Pandas to save the results to a CSV file.
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3 min readIf you want to skip rows with a specific ID in PostgreSQL, you can use the SQL query with a WHERE clause that filters out rows with that ID. You can specify the ID that you want to skip and only select the rows that do not have that specific ID. For example, if you want to skip rows with ID 5, you can write a query like this: SELECT * FROM table_name WHERE id <> 5; This query will only return rows that do not have the ID of 5.