They assume that the Oracle Essbase client was successfully installed. This will bring up a command prompt window. Within the command prompt window, type in esscmd and press the Enter key. If the Oracle Essbase client was installed successfully, the Oracle Essbase command prompt should launch and display the version.
Back to basics A long time ago in a galaxy far, far away…. And guess what, databases have to deal with both situations! The concept The time complexity is used to see how long an algorithm will take for a given amount of data.
To describe this complexity, computer scientists use the mathematical big O notation. This notation is used with a function that describes how many operations an algorithm needs for a given amount of input data.
In this figure, you can see the evolution of different types of complexities. I used a logarithmic scale to plot it.
In other words, the number of data is quickly increasing from 1 to 1 billion. We can see that: The O log n stays low even with billions of data. The worst complexity is the O n2 where the number of operations quickly explodes.
The two other complexities are quickly increasing.
Examples With a low amount of data, the difference between O 1 and O n2 is negligible. Indeed, current processors can handle hundreds of millions of operations per second. This is why performance and optimization are not an issue in many IT projects.
To give you an idea: A bad sorting algorithm has an O n2 complexity Note: There are multiple types of time complexity: I only talked about time complexity but complexity also works for: You can read this article on Wikipedia for the real asymptotic definition.
Merge Sort What do you do when you need to sort a collection? You might not understand right now why sorting data is useful but you should after the part on query optimization. Moreover, understanding the merge sort will help us later to understand a common database join operation called the merge join.
Merge Like many useful algorithms, the merge sort is based on a trick: This operation is called a merge. You can see on this figure that to construct the final sorted array of 8 elements, you only need to iterate one time in the 2 4-element arrays. Since both 4-element arrays are already sorted: Then you take the rest of the elements of the other array to put them in the 8-element array.
If it can help you, I see this algorithm as a two-phase algorithm: The division phase where the array is divided into smaller arrays The sorting phase where the small arrays are put together using the merge to form a bigger array.
Division phase During the division phase, the array is divided into unitary arrays using 3 steps. How do I know that? The idea is that each step divides the size of the initial array by 2. The number of steps is the number of times you can divide the initial array by two.
This is the exact definition of logarithm in base 2. Sorting phase In the sorting phase, you start with the unitary arrays. The power of the merge sort Why this algorithm is so powerful? The idea is to load in memory only the parts that are currently processed.XML Data Type and Columns (SQL Server) 03/14/; 11 minutes to read Contributors.
In this article APPLIES TO: SQL Server (starting with ) Azure SQL Database Azure SQL Data Warehouse Parallel Data Warehouse This topic discusses the advantages and the limitations of the xml data type in SQL Server, and helps you to .
Troels' links: Relational database systems —Focusing on the SQL-standard, hierarchical and temporal data, and open source software. When it comes to relational databases, I can’t help thinking that something is missing.
They’re used everywhere. There are many different databases: from the small and useful SQLite to the powerful Teradata. XML Data Type and Columns (SQL Server) 03/14/; 11 minutes to read Contributors.
In this article APPLIES TO: SQL Server (starting with ) Azure SQL Database Azure SQL Data Warehouse Parallel Data Warehouse This topic discusses the advantages and the limitations of the xml data type in SQL Server, and helps you to choose how to store XML data. The Hierarchical Data Model. The Hierarchical Data Model structures data in a tree of records, with each record having one parent record and many children.
For the sake of our discussion a relational database is a persistent storage mechanism that enables you to both store data and optionally implement functionality.