SQL Server Transparent Data Encryption, also known as TDE, is a “data at rest” encryption mechanism that is introduced in SQL Server 2008 as an Enterprise Edition feature. TDE is used to perform a real-time I/O encryption for the SQL Server database data, log, backup and snapshot physical files, rather than encrypting the data itself, using either Advanced Encryption Standard (AES) or Triple DES (3DES) encryption.
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Microsoft SQL Server has many important features when it comes to file structures. Generally speaking, DBAs often ignore file structures and growth configurations. More specifically, the SQL Server Log files are often left at default values and never touched, even when they begin to cause problems caused. These Log files are important and critical part of the database, especially when it comes to large systems.
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The TOP keyword in SQL Server is a non-ANSI standard expression to limit query results to some set of pre-specified rows. As an argument, it takes 0 to positive Bigint (9223372036854775807) and anything beyond or less gives an error message. TOP without an order by clause, in production, seems buggy because it can produce results in any order depending on the current schema and execution plan. You can also specify a percent with TOP expression which returns only the expression percent of rows from the result set. Float expressions used in TOP percent are rounded up to the next integer value.
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In the articles How to partition an SSAS Cube in Analysis Services Multidimensional and Benefits of Partitioning an SSAS Multidimensional Cube, the concept of measure group partitioning is introduced and the advantages are clearly illustrated. One of the biggest advantages of partitioning is partition elimination, where only the partitions necessary to satisfy the query are read instead of all the data.
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The SQL Server Always On Availability Groups concept was introduced the first time in SQL Server 2012 as an enterprise-level high availability and disaster recovery solution that will replace the database mirroring feature. Always On Availability Group provides a high availability solution on the group level, where each group can contain any number of databases that can be replicated to multiple secondary servers known as Replicas.
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This article discusses a simple solution of how to monitor SQL service availability across multiple servers and reporting. To build this I’ll use SQL Server with simple PowerShell script and cmdlets which generate JSON data and displays results in HTML
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Starting with SQL Server 2016 and Windows Server 2016 there have been numerous cloud related enhancements, most of them are tightly related to Microsoft’s Azure like the ‘Cloud Witness’ but there are others that can be implemented within other public or private clouds.
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SQL Server retrieves data from two areas; memory and disk. As disk operations are more expensive in terms of IO which means they are much slower SQL stores and retrieves data pages from an area known as the Buffer Pool where operations are much faster.
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A SQL Server Computed Column is a virtual column that is not stored physically on the table, unless it is previously specified as PERSISTED. A computed Column value is calculated using a specific expression that can be constant, function, data from other columns on the same table or a combination of these types connected together by one or more operators.
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It is common assumption that an Index Seek operation in a query plan is optimal when returning a low number of output rows. In a scenario involving residual predicates, an Index Seek operation could be reading a lot more rows than it needs into the memory, then each row is evaluated and discarded in memory based on the residual predicate and returns low number of output rows.
This article will explain the concept and the impact of Residual Predicates in a SQL Server Index Seek operation.
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Microsoft SQL Server 2014 is considered to be the first version that supports Hybrid Cloud by adding a lot of exciting new features.
In this article, I will cover some of the top new features in these main points including Hekaton and Hybrid Cloud enhancements:
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When you run a query in SQL Server, the SQL Server Query Optimizer will draw the road map for that query, specifying the optimal way to execute it, which is called the query execution plan.
Generating the execution plan will take few milliseconds from the CPU cycles, which is negligible for one query or small load, but it will be considerable for a very heavy transactional workload. Because of this, SQL Server caches these generated plans in a special type of memory called the Plan Cache to eliminate the overhead generated by the query plan if the same query is executed again. When you submit your query to the SQL Server Engine, it will search in the plan cache if there is any existing execution plan that can be reused, if an available execution plan is found in the plan cache, the plan will be used to execute that query, otherwise, the SQL Server Query Optimizer will create a new plan and keep it in the plan cache for future use.
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To improve performance, it is common for DBAs to search in each aspect except analyzing storage subsystem performance even though in many times, issues are, in fact, caused by poor storage subsystem performance. Therefore, I want to give you some tools and recommendation that you can use it to prevent your storage subsystem from being a performance issue for you.
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SQL Server is a very powerful tool and wherever I go, I see the tool being way much underutilized. Some people even don’t know about the features which are already in the SQL Server and they have not used it, like SQL Server Extended Events. Though, Extended Events is a way more complex and detailed topic which I cannot cover in just one article I will discuss one of its very good utilities out of the countless.
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The following article applies to SQL Server versions 2008 +
Adequate memory is one of the most important factors for a well-functioning instance of SQL Server. By design SQL Server manages its own memory allocations via the SQLOS rather than having the servers Operating System perform this task.
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As DBAs, we all get to the point where we are asked to setup a new server for a specific environment. Setting up a new server is not a big thing but giving the answer to the question that “how well it will work” might be tricky.
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If you are maintaining a very large database, you might be well aware of the pain to perform update statistics on a very large table.
This article introduces incremental statistics which is available from SQL Server 2014 highly simplifies statistics management on very large partitioned tables.
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SQL Server temp tables are a special type of tables that are written to the TempDB database and act like regular tables, providing a suitable workplace for intermediate data processing before saving the result to a regular table, as it can live only for the age of the database connection.
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I work for a large, multinational financial institution. Like most companies in this field, ours is conservative and subject to much regulatory oversight. The first has meant that we’re slow to adopt new technologies. We need to be really, really, really sure things won’t break, customer accounts won’t vanish or lose their balances and that the regulators will not raise any red flags. Everything we do is subject to the scrutiny of our internal auditors, even something that seems simple, like rerunning a production job that failed because the host compute was down. I really mean everything!
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TempDB usage can be considered as a performance bottleneck for workloads that use SQL temp tables and table variables intensively resulted in heavy IO usage. A valuable alternatives for the SQL temp table and table variable are SCHEMA_ONLY Memory-Optimized tables and the Memory-optimized Table Variable, where the data will be completely stored in the memory without the need to touch the TempDB database, providing the best data access performance. SCHEMA_ONLY Memory-Optimized table and the Memory-optimized Table Variable are stored only in the memory with no related component in the disk. It involves no IO activity or TempDB utilization. It can also participate in the transactions without the need to log the transactions.
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Once collected, job performance metrics can be used for a variety of reporting needs, from locating jobs that are not performing well to finding optimal release windows, scheduling maintenance, or trending over time. These techniques allow us to maintain insight into parts of SQL Server that are often not monitored enough and prevent job-related emergencies before they become emergencies.
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Troubleshooting SQL Server is all about gathering the right evidence. Ordinarily we utilise a variety of different methods and analyse their output to look for specific areas where we would focus our diagnostic efforts. We could for example, use the results of various DMVs to look at wait statistic and resource information to help us focus our investigation in a particular area of SQL Server.
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Keeping track of our SQL Server Agent jobs is a very effective way to control scheduling, failures, and understand when undesired conditions may be manifesting themselves. This is a brief journey towards a solution that provides us far greater insight into our jobs, schedules, and executions than we can glean from SQL Server by default.
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As we progress in our career as a SQL Server Database Administrators we encounter situations where managing and monitoring a large number of SQL Servers is the daily job requirement. Monitoring SQL Server is a very vast and detailed area of study. Out of all the monitoring the very basis and critical monitoring in the Resource Utilization Monitoring for SQL Server.
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