SQL Server

LINQPad script to Generate SQL Server Database Restore Script from Ola Hallengren’s Backup Solution

by

Unless you perform regular restores of your database backups, you don’t know that you actually have a valid backup. In a career spanning over 30 years, I’ve seen two occasions where a company was performing backups (or so they thought!) and sending tapes offsite, assuming they were good when in fact the tapes were blank!

The majority of SQL Server installations use Ola Hallengren’s maintenance solution (and certainly all the ones I’ve had anything to do with).

If you are doing regular (5 minutes or less) transaction log backups, a restore might involve applying quite a few transaction logs.

I’ve written a short LINQPad script here which will generate the TSQL to perform a database restore either from a point in time or the latest available, based upon the default locations and naming conventions used by Ola’s backups. It’s Differential backup aware, as well as creating the multiple Transaction Log restore statements. It’s also takes into account where backups are split into separate backup files (which is quite common). You specify the server name, the database name, the root folder where the backups are stored, and either a point in time or the latest.

Disclaimer: Use at your own risk AND test thoroughly!

Example output:

USE [master]

RESTORE DATABASE [AdventureWorks] FROM 
   DISK = N'C:\temp\Backup\K7\AdventureWorks\FULL\K7_AdventureWorks_FULL_20211118_151558.bak'
 WITH NORECOVERY, REPLACE

RESTORE DATABASE [AdventureWorks] FROM 
   DISK = N'C:\temp\Backup\K7\AdventureWorks\DIFF\K7_AdventureWorks_DIFF_20211118_152101.bak'
 WITH NORECOVERY

RESTORE DATABASE [AdventureWorks] FROM 
   DISK = N'C:\temp\Backup\K7\AdventureWorks\LOG\K7_AdventureWorks_LOG_20211118_152226.trn'
 WITH NORECOVERY, STOPAT = '2021-11-21 17:07:22'

RESTORE DATABASE [AdventureWorks] WITH RECOVERY

Tuning SQL Server Queries 101

by

First, get an actual query execution plan. Look for warnings in the query plan.

Basic

  • First look for large scans and lookups: these can often be resolved by creating a new index or extending an existing one with additional included columns. Seeks are usually preferable to scans.
  • Then look for significant variance of Actual versus Estimated row counts: you can provide the optimiser with more accurate information by updating statistics, creating new statistics objects, adding statistics on computed columns, or by breaking the query up into simpler parts. Might be caused by ‘parameter sniffing’.
  • Then look for expensive operators in the query plan, especially those that consume memory such as sorts and hashes. Sorting can sometimes be avoided by altering/adding indexes.

More Advanced

Joe Sack has an excellent walkthrough here: The Case of the Cardinality Estimate Red Herring

SQLFrontline Freemium Edition

by

I’ve recently changed what I was calling the ‘Demo’ version of SQLFrontline, to a ‘Freemium’ model. The demo version only displayed one recommendation result in each of the four severity categories (Critical, High, Medium, Info).

The free version does not include all the features of the paid premium version obviously, but still provides some useful recommendations, providing advice on 40 checks.

Both use the same lightweight metadata collection.

The Free Version:

  • Performs 40 checks (out of 350+), but doesn’t show all affected objects if a check results in a recommendation
  • Deletes all collected metadata after collection
  • No reminder list is shown
  • Does not display a list of issues that are no longer present since last collection
  • Sends a single email for all servers
  • No database specific recommendations are made
  • Can only collect metadata for a limited number of servers

The Premium Version:

  • 350+ checks performed across the categories of Configuration, Reliability, Performance, Security, Server Info, Table/Index Design
  • New checks are constantly being added
  • Reminder list of recommendations that have been made previously and not yet fixed
  • List of issues fixed compared to the last collection
  • Can choose how long to store collected metadata, so that point in time reports can be made, along with automated estimates of DB growth over time
  • Can send 1 email per server or a single email for all servers
  • Ability to ‘mute’ recommendations on an individual basis, or entire check (for non-critical checks)
  • No practical limit on the number of servers

If you want to try it out, click this link to request a free access token.

Once you have an access token, here’s how to run it: How to run SQLFrontline

Don’t Embed SQL into SSRS Reports

by

Reasons not to embed SQL in SSRS reports (.rdl) and create stored procedures instead:

  • Easier to version control in SCC
  • Better visibility in the database
  • Easier to debug
  • Easier to fix any performance problems (and to hot fix, if necessary)
  • Easier to re-use functionality (which is often lengthy to produce) with other systems/APIs etc
  • Stored Procedures get given a name that accurately describes what they do
  • Easier to gather execution statistics
  • Easy to see what parameters are used to filter
  • Can be secured with explicit permissions
  • Easier to write automated testing against a stored procedure

All seem fairly obvious, but it’s surprising how many people still embed SQL into SSRS reports.

Configurable Retry Logic in Microsoft.Data.SqlClient

by

Microsoft have recently released a long awaited retry mechanism for .NET SqlClient

I’m a fan of Polly for retry logic:

Polly is a library that allows developers to express resilience and transient fault handling policies such as Retry, Circuit Breaker, Timeout, Bulkhead Isolation, and Fallback in a fluent and thread-safe manner.

It will be interesting to see how they compare in terms of ease of use.

Configurable retry logic in SqlClient introduction

Date and Time Dimension

by

Almost every fact table in a data warehouse uses a date (or calendar) dimension, because most measurements are defined at specific points in time. A flexible calendar date dimension is at the heart of most data warehouse systems; it provides easy navigation of a fact table through user familiar dates, such as weeks, months, fiscal periods and special days (today, weekends, holidays etc.).

I’ve created a date dimension generator here at Github

It targets SQL Server, but should be easy to convert to other RDBMS.

It features:

  • User defined start and end dates
  • Computed Easter dates (for years 1901 to 2099)
  • Computed Chinese New year dates for years 1971 to 2099.
  • Computed public holidays for US, UK, Canada, Ireland, Malta, Philippines, Australia (with state specific for WA, NSW, QLD, SA, VIC).
  • Date labels in US, UK and ISO formats.

Things to Note:

  1. The [TodayFlag] needs to be updated once per day by a scheduled task (timezone dependent: might need a flag for each timezone).

  2. If you use an unusual Fiscal year (say 5-4-4), it will need to be loaded from an external source (such as an Excel/Google spreadsheet).

  3. The precise start date of the month of Ramadan is by proclamation, so these need to be added, year by year. It is possible to calculate but can be a day out, and can vary by region.

    https://travel.stackexchange.com/questions/46148/how-to-calculate-when-ramadan-finishes

    https://en.wikipedia.org/wiki/Ramadan_%28calendar_month%29

Babelfish for PostgreSQL

by

This has the capacity to be huge:

Babelfish for PostgreSQL is an Apache-2.0 open source project that adds a Microsoft SQL Server-compatible end-point to PostgreSQL to enable your PostgreSQL database to understand the SQL Server wire protocol and commonly used SQL Server commands. With Babelfish, applications that were originally built for SQL Server can work directly with PostgreSQL, with little to no code changes, and without changing database drivers.

Do You Name All Your SQL Server Database Constraints?

by

If you define a constraint without explicitly giving it a name, SQL Server will generate one for you.
You know the ones, they look something like this PK__MY_TABLE__3213E83FA7739BB4.

Why might that be a bad thing? It makes writing deployment scripts harder because you won’t know up front the names of constraints you might want to refer to.

Michael J Swart describes a query to discover the system generated names in your databases (with a small modification):

SELECT 
    [Schema] = SCHEMA_NAME(o.schema_id),
    [System Generated Name] = OBJECT_NAME(o.object_id),
    [Parent Name] = OBJECT_NAME(o.parent_object_id),
    [Object Type] = o.type_desc
FROM 
    sys.objects o
    JOIN sys.sysconstraints c ON o.object_id = c.constid
WHERE 
    (status & 0x20000) > 0
    and o.is_ms_shipped = 0

According to the sys.sysconstraints documentation page:

This SQL Server 2000 system table is included as a view for backward compatibility. We recommend that you use the current SQL Server system views instead. To find the equivalent system view or views, see Mapping System Tables to System Views (Transact-SQL). This feature will be removed in a future version of Microsoft SQL Server. Avoid using this feature in new development work, and plan to modify applications that currently use this feature.

You can query the same information by using the individual views unioned together:


SELECT 
    [Schema] = SCHEMA_NAME(schema_id),
    [System Generated Name] = OBJECT_NAME(object_id),
    [Parent Name] = OBJECT_NAME(parent_object_id),
    [Object Type] = type_desc
FROM sys.check_constraints 
WHERE is_system_named = 1

UNION ALL

SELECT 
    [Schema] = SCHEMA_NAME(schema_id),
    [System Generated Name] = OBJECT_NAME(object_id),
    [Parent Name] = OBJECT_NAME(parent_object_id),
    [Object Type] = type_desc
FROM sys.default_constraints 
WHERE is_system_named = 1

UNION ALL

SELECT 
    [Schema] = SCHEMA_NAME(schema_id),
    [System Generated Name] = OBJECT_NAME(object_id),
    [Parent Name] = OBJECT_NAME(parent_object_id),
    [Object Type] = type_desc
FROM sys.key_constraints 
WHERE is_system_named = 1

UNION ALL

SELECT 
    [Schema] = SCHEMA_NAME(schema_id),
    [System Generated Name] = OBJECT_NAME(object_id),
    [Parent Name] = OBJECT_NAME(parent_object_id),
    [Object Type] = type_desc
FROM sys.foreign_keys  
WHERE is_system_named = 1

SQL Server Error Code 4815 Bulk Insert into Azure SQL Database

by

If you receive error code 4815 while doing a Bulk Insert into an Azure SQL Database (including SqlBulkCopy()), it’s likely you are trying to insert a string that is too long into a (n)varchar(x) column.

The unhelpful error message does not contain any mention of overflow, or the column name! Posting in the hope it will save someone some time.