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70-762 - Developing SQL Databases - Dump Information

Vendor Name : Microsoft
Exam Code : 70-762
Exam Name : Developing SQL Databases
Questions and Answers : 85 Q & A
Updated On : December 13, 2018
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Microsoft 70-762 Exam (Developing SQL Databases) Detailed Information

70-762 - Developing SQL Databases


70-762 Test Objectives


Design and implement database objects (25–30%)
Implement programmability objects (20–25%)
Manage database concurrency (25–30%)
Optimize database objects and SQL infrastructure (20–25%)

70-762 Questions and Answers

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70-762 Developing SQL Databases

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70-762 exam Dumps Source : Developing SQL Databases

Test Code : 70-762
Test Name : Developing SQL Databases
Vendor Name : Microsoft
Q&A : 85 Real Questions

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Microsoft Microsoft Developing SQL Databases

SolarWinds to showcase extended Microsoft Azure Monitoring Capabilities at SQL Server reside! 360 2018 | killexams.com Real Questions and Pass4sure dumps

AUSTIN, Texas, Nov 28 (Bernama) -- SolarWinds (NYSE:SWI), a number one issuer of potent and low-budget IT management utility, nowadays introduced its participation at SQL Server live! 360 2018, December 2-7, 2018, in Orlando, Florida. SolarWinds will display the newest updates to its Microsoft® Azure® capabilities, designed to supply a simple, potent adventure for full-stack monitoring, root trigger analysis, and optimized efficiency for DevOps and IT authorities working on-prem, in the cloud, or in hybrid environments.

Microsoft named SolarWinds Head Geek™ Thomas LaRock a ten-time Most useful knowledgeable (MVP) for demonstrating his deep dedication to helping others make the most of their Microsoft technology. With greater than two decades of IT event, LaRock has served within the roles of programmer, developer, analyst, and database administrator. he is a Microsoft licensed grasp, VMware® vExpert™, and Microsoft licensed trainer.

For the entire textual content, click here

Microsoft pronounces SQL Server 2017 Launch | killexams.com Real Questions and Pass4sure dumps

In-Depth

Microsoft broadcasts SQL Server 2017 Launch

The latest SQL Server comes filled with help for Linux, automated tuning and other enhancements so that you can increase and simplify the use of the database platform.

  • with the aid of Joey D'Antoni
  • 09/25/2017
  • nowadays at the Microsoft Ignite conference, Microsoft announced that SQL Server 2017 can be commonly accessible on Oct. 2. This comes handiest 15 months or so after launching SQL Server 2016. Microsoft's swift construction capability extra common releases, which grants more cost to shoppers who pay for software Assurance (SA). It also ability that extra elements are delivered greater commonly, which aligns to their Azure SQL Database platform, which is usually up-to-date on a month-to-month basis. To reply essentially the most critical question, the licensing mannequin and charges are exactly the same as they have been for SQL Server 2016.

    SQL Embraces LinuxThe massive information with the unlock of SQL Server 2017, is that it's the first time SQL Server is attainable on the Linux platform. Microsoft releasing one among its important utility platforms on Linux is massive, and represents Microsoft's shift towards being a extra open supply-oriented business. The Linux distributions supported consist of RedHat enterprise Linux, SuSE commercial enterprise Linux and Ubuntu. that you could additionally run SQL Server 2017 in Docker containers, which is an choice many development stores might also agree with for quick deployment of development databases.

    SQL Server on Linux makes use of the identical code as SQL Server 2017 on windows, except for a platform abstraction layer that manages OS-certain calls.

    "SQL Server on Linux is an engineering feat.  or not it's the equal first-rate, secure, high performance, prosperous database engine that we now have all come to grasp on windows, yet it's absolutely native to Linux," talked about Travis Wright, principal software manager at Microsoft.  "The database engine binaries you deploy on home windows and Linux are actually the same actual information right down to the byte." i will attest that even features like energetic directory authentication, backup, and repair all work simply the same as on home windows.

    one of the most key desires with SQL Server on Linux is greater accessibility for builders who're used to engaged on different database platforms. in addition to the database engine and tools, SQL Server Integration features is obtainable on Linux, and i can be stunned if Microsoft didn't port the other accessories of the SQL Server platform to Linux ultimately. Licensing SQL Server on Linux uses the same model as home windows. although, Microsoft is engaging in a unique discounted subscription mannequin along with red Hat to present OS and RDBMS licensing on a lease model.

    different predominant aspects Arriving with SQL Server 2017So, you have got heard a lot about SQL Server 2017 on Linux, but what else is there? SQL Server 2017 introduces a lot of new features that might be desirable to you no matter if you're a database administrator, a developer, or an analyst.

    automated Tuning: whereas many database carriers have claimed to have self -tuning databases in the past, Microsoft has built intelligence into a group of self-tuning elements in SQL Server 2017. Microsoft has learned an awful lot from aiding Azure SQL Database and determining client efficiency complications. operating a database provider that features millions of databases makes it possible for for deeper insight into how valued clientele use the product, and where their headaches are. they've taken that potential and mixed it with the question shop, a characteristic added in SQL Server 2016, which tracks question execution plans and runtime information. This allows the database engine to determine queries that have regressed in efficiency, and changed execution plans (the route the engine takes to get the query's facts). If the engine determines that a change in plan has happened, and the question has regressed in performance, the engine will revert to a outdated plan.

    "whether it is three a.m. in the morning, automatic Plan Correction helps mitigate efficiency considerations due to plan regression situations with out guide intervention," stated Joe Sack, precept software manager at Microsoft. "Then in the event you are available that next morning that you would be able to study see what happened and work on root cause analysis. " There a few other optimizations in area in SQL Server 2017, concentrated on making tricky question operations go faster.

    Graph Database: one in all my favourite features is the introduction of a graph engine into SQL Server. Graph databases are normal to music relationships or hierarchies, a spot the place relational databases have struggled when it comes to structure and efficiency. Graph databases are implemented by the use of nodes (or vertices) and edges (or relationships). for instance, you could say John is chums with Jane, and Jane is chums with Becky. whereas there had been a number of small graph database tasks, many have not supported the SQL language, and integration with different systems. with the aid of bringing graph into SQL Server 2017, users can take competencies of native SQL, together with the new in shape operator to perform graph queries.

    Resumable online Index Rebuild: As someone who has been a database administrator for approach too long, this characteristic has enormous enchantment to me. Indexes get fragmented as updates and deletes occur, and wish to be reorganized and rebuilt periodically. Performing these operations are very IO intensive, and are frequently run right through renovation home windows. however on greater programs some operations may also run past the window and ought to be aborted, or more often, conveniently don't seem to be run. Resumable index rebuild allows you to time table mounted window on your preservation operations (for instance, allocating three hours an evening to index preservation); or without difficulty pause and resume them manually. This function will change the techniques DBAs operate database preservation.  

    every thing Else: one of the vital different elements blanketed during this unlock are more desirable efficiency for backups, more enhancements to the In-memory OLTP characteristic and integration of the standard energy query tool with SQL Server evaluation features. Microsoft also released a extremely enjoyable enhancement to its superior analytics features by means of including a predict operator to the T-SQL programming area. This can also be a very speedy solution to function evaluation on a pre-existing R or Python model.

    As you deploy SQL Server 2017, it is vital to word that each SQL Server management Studio and SQL Server Reporting features are now separate installs from the database engine and different add-ons. administration Studio has a distinct release cycle from SQL Server and is updated monthly.

    about the creator

    Joseph D'Antoni is an Architect and SQL Server MVP with over a decade of experience working in both Fortune 500 and smaller organisations. he's at the moment major consultant for Denny Cherry and associates Consulting. He holds a BS in computing device counsel techniques from Louisiana Tech tuition and an MBA from North Carolina State university. Joey is the co-president of the Philadelphia SQL Server clients community . he is a general speaker at move Summit, TechEd, Code Camps, and SQLSaturday events.


    Microsoft broadcasts Elastic SQL Database pools For Azure | killexams.com Real Questions and Pass4sure dumps

    developers and impartial application providers who regularly run a whole lot — and even thousands — of separate databases for their customers now have a brand new choice to manipulate them while maintaining prices predictable.

    As Microsoft nowadays announced throughout its build developer conference keynote in San Francisco, its new Azure SQL Database elastic databases (yep, that’s the complete name) enable builders to collect their databases right into a single pool to be sure they don’t over-provision selected databases simplest to be able to contend with top demand.

    As Microsoft’s company VP for its information platform T.k. “Ranga” Rengarajan told me previous this week, Microsoft discovered that a lot of its valued clientele had been partitioning their clients into distinctive databases. All of these databases have distinct aid requirements — “and people are largely unpredictable,” he mentioned. “What we realized is that these SaaS carriers want new tools to control and video display these databases.”

    2I8A9137

    With these elastic database pools, purchasers pay for the combination of all the databases as an alternative of for every one one at a time. whereas it’s hard to predict the wants of each diverse database shard, the combination is pretty predictable, Microsoft argues, and that makes it more straightforward for organizations to manipulate their database wants with this new service.

    Microsoft additionally says that this new database classification will permit corporations to extra with ease run centralized queries and reporting tools across all of their databases. different elements of the brand new provider include full-textual content search inside databases, column-degree entry rights (some thing Microsoft additionally lately introduced for the typical Azure SQL databases), and precise-time encryption of information and logs.

    These new facets are now obtainable throughout the Azure Portal.


    70-762 Developing SQL Databases

    Study Guide Prepared by Killexams.com Microsoft Dumps Experts


    Killexams.com 70-762 Dumps and Real Questions

    100% Real Questions - Exam Pass Guarantee with High Marks - Just Memorize the Answers



    70-762 exam Dumps Source : Developing SQL Databases

    Test Code : 70-762
    Test Name : Developing SQL Databases
    Vendor Name : Microsoft
    Q&A : 85 Real Questions

    wherein should I searching for to get 70-762 real test questions?
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    Developing SQL Databases

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    MB Software Gets A Handle On Remote SQL Jobs | killexams.com real questions and Pass4sure dumps

    November 28, 2018 Alex Woodie

    System administrators who get frustrated with the inability to see which SQL jobs coming in through ODBC are causing problems on their IBM i server may be interested in a product called Work with Active SQL (WRKACTSQL) from MB Software and Consulting, which recently announced the tool will be free through the end of the year.

    SQL is just about as close to a universal language for business as you can get. While there are other (i.e. “native”) methods of fetching data from Db2 for i, nearly three-quarters of IBM i developers report using SQL, making it the number two most popular development language on IBM i, after RPG (which can use “native” calls or SQL).

    The problem is, not all SQL jobs are created equal. When it comes to administering to an IBM i server that’s processing a large number of SQL jobs, things can get dicey for those charged with ensuring that things run smoothly.

    Every IBM i administrator is familiar with the Work with Active Jobs (WRKACTJOB) command from IBM, which displays every active jobs on the system and tells them which ones are consuming the most resources. WRKACTJOB is a great command.

    However, that command doesn’t always provide the needed level of clarity on all jobs, particularly when remote SQL requests are coming in over the network through the Open Database Connectivity (ODBC) exit point.

    When remote SQL queries consume resources through ODBC and JDBC, WKRACTJOB displays the jobs under the QZDASOINIT heading. Jobs that originate on Web and mobile clients, and even SQL queries fired off from System i Navigator, all fall under this QZDASOINIT umbrella.

    The problem is that administrators have no idea what these QZDASOINIT jobs are doing or what code they’re associated with. All they see is that these QZDASOINIT jobs are consuming a lot of system resources, and they need to address the problem.

    Remote SQL queries are exposed for what they really are with MB Software and Consulting’s WRKACTSQL tool.

    That’s where MB Software and Consulting’s WRKACTSQL tool comes into the picture. The command is designed to give visibility and control over remote ODBC requests by showing the actual SQL statements that are impacting the system in real time, thereby allowing systems administrators to react appropriately.

    According to MB Software and Consulting, WKRACTSQL lets admins hold, terminate, or change run priority for specific SQL requests that running on the system. It also lets them set up alerts to automatically receive notification when a user runs the same SQL request that caused the problem in the first place. The software also lets administrators block specific users and specific SQL requests from getting access to the system.

    MB Software and Consulting normally charges $500 per LPAR for WRKACTSQL. But as part of a promotion unveiled last month, the New York company is giving the tool away for free through December 31. For more information see the company’s website at www.mb-software.com.

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    Tags: Tags: IBM i, JDBC, LPAR, ODBC, Open Database Connectivity, RPG, SQL, WRKACTSQL

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    SQL Prompt Code Analysis: A Hint Is Used (PE004-7) | killexams.com real questions and Pass4sure dumps

    "Because the SQL Server query optimizer typically selects the best execution plan, we recommend that hints be used only as a last resort by experienced developers and database administrators" — Microsoft SQL Server Documentation

    Really, there should be no discussion about this, because the above warning, which is in the documentation, summarizes it so well. However, I feel sympathy with the frustration of database developers who see the ever-increasing range of hints that are available or see the wide use of hints in commercial database applications, some of which sound like they can help solve their query performance problems. The dangers of hints need to be explained.

    SQL Prompt has several performance-related code analysis rules that will warn you of the use of index hints (PE004), join hints (PE005), tables hints (PE006) and query hints (PE007).

    Misuse of Hints

    I was once a development team leader, managing the operations of a telecoms database system. When I found hints in the SQL code, I put out a draconian ban on the use of all hints, except OPTION(RECOMPILE). It caused a little ill-feeling in the group because they could see hints being used in the source of SQL Server, and they felt that it was an acceptable way to fine-tune their SQL. It seemed like the 'Turbo Button' that once adorned the front of PCs that used to make everything run faster.

    I relented to the point that I allowed any hint, as long as the developers were able to explain why they needed it, what it did, what the gain was, the consequences for scalability, and the effects on ACID compliance. I asked them also to prepare a maintenance plan that identified and re-tested all hints in response to changes in the data distribution, in response to an upgrade to a new SQL Server version, or application of a new service pack to verify that the hint still offered optimal performance. The use of hints soon disappeared.

    I would hate to imply that all hints are bad, only the reckless use of them. There will always be a rare requirement for a query hint, possibly, once in a blue moon, a join hint, and even a legendary table hint, despite the scary warnings, Microsoft keep introducing them. Most frequently, hints are used if the Query Optimizer can't produce a good plan or a plan that offers stable performance, which usually happens when it gets its estimate of the number of rows very wrong. This is more likely to happen as queries get more complicated, or they get too clever.

    A better approach, when faced with a query that doesn't get the best plan, is to back off and write it a simpler way. A slow-running query is nature's way of telling you that you're doing something the wrong way. Most often, you are using the wrong approach to get the information, or the database design is flawed in some way. This flaw is most commonly an indexing problem. I've almost never succeeded in successfully 'hinting' away a problem, even in what Microsoft tactfully calls 'the last resort'. I realize that in the real world of pragmatism, it is sometimes impossible to do more than a gaffer-tape remedy, but it is always worth remembering that an act of pragmatism can turn into a time-bomb when you upgrade the SQL Server version or when either the data in the database changes or the indexes are altered and the optimizer can't change the query plan in response.

    Is It OK to Use the NOLOCK Hint?

    Let's take NOLOCK table hint as the classic example. It is misnamed, because the hinted query still obtains a Sch-S (schema stability) lock on the target table and, if used with a data modification statement, also exclusive locks. Really, it just ensures that the hinted query acquires no shared locks on that table and is essentially a directive that dirty reads are allowed, for the duration of the transaction. This means that any data modification transactions running concurrently will not be blocked from modifying data that a NOLOCK query is reading. Also, when the hint is applied to data modification transactions, another query can still read that 'in-flight' data. This means that it might read data that is never committed, perhaps because the hinted transaction subsequently rolls back.

    If you really need to allow dirty reads on a table, for the duration of a transaction, then it's better to use the equivalent, and more informative hint, READUNCOMMITTED. This is as if you had set the query to work at the READ_UNCOMMITTED isolation level. NOLOCK is an anachronism that is already in maintenance mode for data modifications ( UPDATE and DELETE)

    If you do use it then, naturally, in a hard-working OLTP system, you'll get a frequent variety of errors depending on timings, but they can include errors for your transaction (e.g. error 601), incorrect aggregations such as totals, doppelganger data (data seen twice), time-travel data (column data from different 'commits' in the same row) or phantom reads. You can even get index corruption if you use NOLOCK on anything other than a SELECT.

    One might think that query with a NOLOCK table hint is able to do its reckless work regardless of existing locks on table, but it is stopped dead in its tracks when another query holds a Sch-M (schema modification) lock that that is issued by a DDL operation. Also, a DDL operation, such as index maintenance, is prevented by a query using a NOLOCK hint, because it has issued a Sch-S lock.

    If the reason for using the NOLOCK hint is to avoid the overhead of locking and blocking, then a far better approach is to use one of the snapshot-based isolation levels. One option is to allow transactions to use the default READCOMMITTED isolation level, but with the READ_COMMITTED_SNAPSHOT database option set to ' ON '. This means that queries see a transactionally-consistent snapshot of the data as it existed at the start of the statement. This avoids dirty reads, but without the need for transactions to acquire shared read locks.

    To prevent all read phenomena (dirty reads, non-repeatable reads, phantom reads), you can set the ALLOW_SNAPSHOT_ISOLATION database option to ON, and then at the session-level, use the command to specify the SNAPSHOT isolation level. This ensures that statements in a transaction get a snapshot of the committed data as it existed at the start of the transaction.

    Edge Cases for Use of NOLOCK

    One can't say that the use of NOLOCK is always wrong, especially as they are so evident in the source of the metadata functions on SQL Server. They are used there because a higher isolation level runs the risk of causing unwanted contention on non-user data structures. It is very much an edge-case.

    It is difficult to argue that it is wrong to use it where a query must read a high proportion of rows in a large read-only table. However, even where NOLOCK is not a bad choice, it is still better to use isolation levels such as SNAPSHOT, or the snapshot-based version of READCOMMITTED, instead.

    Another edge case is when you must execute diagnostic queries in a production database. The last thing you want to do is to accidentally block other users. In this case, there is value in a NOLOCK even though you can't expect exact values.

    Another time when you might justifiably use hints is as a temporary expedient when you need to test out a badly performing query in development with different query plans to work out why the optimizer isn't using the best-performing strategy. It can lead you to out-of-date distribution statistics or missing columns in a covering index.

    I've heard it suggested that it is fine to use NOLOCK on a database that has only static data in it that isn't going to be changed. However, such databases have a habit of suddenly changing data when you don't expect it. If on the other hand, you set the database to READ_ONLY, you don't need the hint anyway because shared locks aren't taken out for a read-only database.

    Dealing With Bad Hints You Can't Delete

    If you append OPTION(TABLEHINT(<tablename>)) to a query it will override (disable) any other table hints issued by that query. You can enforce this 'override' hint for all queries by adding it to a plan guide. Nobody is upset by the disappearance of a cherished hint, and developers can continue to believe that their hint is really doing a good job (see Override Bad Table Hints with A Plan Guide).

    Conclusion

    Normally, with SQL Server, the features work as advertised. Hints are an exception. They aren't hints at all, but directives. They generally do what they say they do, but it isn't always obvious that there is a big downside: they must be constantly reviewed and assessed as the data changes in either size or distribution, or as the indexing strategy changes. Whenever the SQL Server is upgraded, the hints must be rechecked.

    They remove the query optimizer's free hand and generally condemn the database execution strategy to exist in time warp. When the Query Optimizer is making the wrong choice, it is not because it is stupid, because it isn't. It is because your queries are obtuse, it has the wrong information on which it is making its choice, or you are providing indexes that don't meet the requirements of the queries you make. To make an uncharacteristic biblical reference, using hints is like Balaam using the whip on his donkey because it refuses to move. It turns out that the donkey was more perceptive than he was.

    Using hints is like Balaam using the whip on his donkey because it refuses to move.


    How to Source Control Your Databases for DevOps | killexams.com real questions and Pass4sure dumps

    Key Takeaways
  • Database schema, including indexes, need to be in source control.
  • Data that controls business logic such as lookup tables also need to be in source control.
  • Developers need a way to easily create local databases.
  • Shared database should only be updated via a build server. 
  • A robust DevOps environment requires having continuous integration for every component of the system. But far too often, the database is omitted from the equation, leading to problems from fragile production releases and inefficient development practices to simply making it harder to onboard new programmers.

    In this article, we discuss the unique aspects of databases, both relational and NoSQL, in a successful continuous integration environment.

    The first issue to be addressed is source control and schemas. It is not appropriate to have developers apply database changes in an ad hoc manner. That would be the equivalent to making changes to JavaScript files by editing them directly on the production server.

    When planning your source control for the database, make sure you capture everything. This includes, but is not limited to:

  • Tables or Collections
  • Constraints
  • Indexes
  • Views
  • Stored Procedures, Functions, and Triggers
  • Database configuration
  • You may be thinking, “I’m using a schemaless database so I don’t need source control”. But even then, you are going to need to account for indexes and overall database configuration settings. If your indexing scheme is different in your QA and production database, it will be very difficult to perform meaningful performance tests.

    There are two basic types of source control for databases, which we’ll call “whole-schema” and “change script”.

    Whole-Schema Source Control

    “Whole-schema” source control is where your source control looks like the way you want your database to look. When using this pattern, you can see all the tables and views laid out exactly as they are meant to be, which can make it easier to understand the database without having to deploy it. 

    An example of whole-schema source control for SQL Server is SQL Server Data Tools(SSDT). In this tool all of your database objects are expressed in terms of CREATE scripts. This can be convenient when you want to prototype a new object using SQL, then paste the final draft directly into the database project under source control. 

    Another example of whole-schema source control is Entity Framework Migrations. Instead of SQL scripts, the database is primarily represented by C#/VB classes. But again, you can get a good picture of the database by browsing the source code.

    When working with whole-schema source control, you usually don’t write your migration scripts directly. The deployment tools figure out what changes are needed for you by comparing the current state of the database with the idealized version in source control. This allows you to rapidly make changes to the database and see the results. When using this type of tool, I rarely alter the database directly and instead allow the tooling to do most of the work. 

    Occasionally the tooling isn’t enough, even with pre- and post- deployment scripts. In those cases, the generated migration script will have to be hand-modified by a database developer or DBA, which can break your continuous deployment scheme. This usually happens when there are major changes to a table’s structure, as the generated migration script can be inefficient in these cases.

    Another advantage of whole-schema source control; it supports code analysis. For example, if you alter the name of a column but forget to change it in a view, SSDT will return a compile error. Just like static typing for application programming languages, this catches a lot of errors and prevents you from attempting to deploy clearly broken scripts. 

    Change Script Source Control

    The other option is “change script” source control. Instead of storing the database objects themselves, you store the list of steps necessary to create the database objects. The one I’ve used successfully in the past is Liquibase, but they all work pretty much the same. 

    The main advantage of a change script tool is you have full control of what the final migration script will look like. This makes it easier to perform complex changes such as when tables are split or combined.

    Unfortunately, there are several disadvantages to this style of source control. The first is the need to write the change scripts. While it does give you more control, it is also very time consuming. It is much easier to just add a property to a C# class than to write out the ALTER TABLE script in longhand.

    This becomes even more problematic when working with things like SchemaBinding. For those who are unfamiliar with the term, this enables some advanced features in SQL Server by locking down the table schema. If you make changes to a table or view’s design, you have to first remove the SchemaBinding from any views touching the table or view. And if those views are schema-bound by other views, they too need to be temporarily unbound. All of this boilerplate, while easy for a whole-schema source control tool to generate, is hard to do correctly by hand.

    Another disadvantage of change script tools is they tend to be very opaque. For example, if you want to know the columns on a table without deploying it, you need to read every change script that touches the table. This makes it really easy to miss something. 

    Which source control model to use?

    When starting a new database project from scratch, I always choose whole-schema source control when available. This allows developers to work much faster and requires less knowledge to use successfully so long as you have one person to set it up.

    For existing databases, especially ones in production for a number of years, change script source control is often more appropriate. Whole-schema tools make certain assumptions about the database design, while change script tools work with any database. Also, whole-schema tools are harder to build so they may simply be not available for your particular database.

    Tables can be broadly classified as “managed”, “user”, or “hybrid” depending on the nature of the data they contain. The way you treat these tables is different depending on which category it falls into.

    Managed Tables

    A common mistake when putting databases under source control is forgetting the data. Invariably there are going to be “lookup tables” that hold data which users are not meant to modify. For example, this could contain table-drive logic for business rules, the various status codes for a state machine, or just a list of key-value pairs that match an enum in the application code.

    The data in this type of table should be treated as source code. Changes to it need to go through the same review and QA process you would use for any other code change. And it is especially important the changes are automatically deployed along with other application and database deployments, otherwise those changes may be accidentally forgotten.

    In SQL Server Data Tools, I handle this using a post-deployment script. In this script, I populate a temporary table with what the data should look like, then use a MERGE statement to update the real table. 

    If your source control tool doesn’t handle this well, you could also build a stand-alone tool to perform the data updates. What’s important isn’t how you do it, but whether or not the process is easy to use and reliable.

    User tables are any table where a user can add or modify data. For our purposes, this includes both tables they can modify directly (e.g. name & address) and tables modified indirectly by their actions (e.g. shipping receipts, logs). 

    Real user data is almost never directly added to source control. However, it is a good practice to have realistic looking sample data available for development and testing. This could be directly in the database project, stored elsewhere in source control, or if particularly large, kept on a separate file share.

    Hybrid Tables

    A hybrid table is one that stores both managed and user data. There are two ways this can be partitioned. 

    A column partition is when users can modify some columns, but not others. In this scenario, you treat the table just like a normal managed table but with the additional restriction, you never update a user-controlled column. 

    A row partition is when you have certain records users cannot modify. A common scenario I run into is the need for hard-coded values in the Users table. On larger systems, I may have a separate user ID for each micro-service that can make changes independently from any real person. For example, a user may be called “Bank Data Importer”. 

    The best way I have found for managing row-partitioned hybrid tables is via reserved keys. When I define the identity/auto-number column, I’ll set the initial value at 1,000, leaving users 1 through 999 to be managed through source control. This requires a database that allows you to manually set a value in an identity column. In SQL Server, this is done via the SET IDENTITY_INSERTcommand. 

    Another option for dealing with this scenario is to have a column called “SystemControlled” or something to that effect. When set to 1/true, it means the application will not allow direct modifications. If set to 0/false, then the deployment scripts know to ignore it.

    Once you have the schema and data under source control, you can take the next step and start setting up individual developer databases. Just as each developer should be able to run their own instance of a web server, each developer who may be modifying the database design needs to be able to run their own copy of the database.

    This rule is frequently violated, to the determent of the development team. Invariably developers making changes to a shared environment are going to interfere with each other. They may even get into “deployment duels”, where two developers each try to deploy changes to the database. When this happens with a whole-schema tool, they will alternately revert the other’s changes without even realizing it. If using a change-script tool, the database may be placed in an indeterminate state where the migration scripts no longer work and it needs to be restored from backups.

    Another issue is schema drift. This is when the development database no longer matches what’s in source control. Over time, developer databases tend to accumulate non-production tables, test scripts, temporary views, and other cruft to be cleared out. This is much easier to do when each developer has their own database they can reset whenever they want.

    The final and most important issue is that service and UI developers need stable platform to write their code. If the shared database is constantly in flux, they can’t work efficiently. At one company I worked at, it was not usual to see developers shout, “services are down again” and then spend an hour playing video games while the shared database was put back together.

    The number one rule for a shared developer or integration database is no one should be modifying the database directly. The only way a shared database should be updated is via the build server and the continuous integration/deployment process. Not only does this prevent schema drift, it allows scheduled updates to reduce disruptions.

    As a rule of thumb, I allow the shared developer database to be updated whenever a check-in is made the relevant branch. This can be somewhat disruptive, but usually it is manageable. And you do need a place to verify the deployment scripts before they hit integration.

    For my integration databases, I tend to schedule deployments to happen once per day along with any services. This provides a stable platform which UI developers can work against. Few things are as frustrating to UI developers as not knowing if code that suddenly starts failing was their mistake or a problem in the services/database.

    An often-overlooked aspect of database management is security. Specifically, which users and roles have access to which tables, views, and stored procedures. In the all too familiar worst-case scenario, the application gets full access to the database. It can read and write to every column of every table, even ones it has no business touching. Data breaches often result from exploitations of   flaws in a minor utility application with far more access rights than it needs. 

    The main objection to locking down the database is, “we don’t know what will break”. Because it has never been locked down before, developers literally have no idea what permissions the application actually needs.

    The solution to this is to put the permission in source control from day one. This way, when the developer tests the application, it will fail from the onset if the permissions are incorrect. This in turn means by the time it gets to QA, all the permissions are settled and there is no guesswork or risk of a missing permission.

    Depending on the nature of your project, containerization of the database is an optional step. To illustrate why, I’ll offer two use cases.

    For our first use case, the project has a very simple branching structure: there is a “dev” branch that feeds into a QA branch, which in turn feeds into Staging and finally Production. This can be handled by four shared databases, one for each stage in the pipeline.

    In the second use case, we have a set of major feature branches. Each major feature branch is further subdivide into a dev and QA branch. Features have to pass QA before becoming candidates for merging into the main branch, so each major feature needs its own test environment.

    In the first use case, containerization is probably a waste of time even if your web services do need containers. For the second use case, containerization of some sort is critical. If not real containers (e.g. Docker), then at least deployment scripts that can generate new environments as needed (e.g. AWS or Azure) when creating new major feature branches. 

    About the Author

    Jonathan Allen got his start working on MIS projects for a health clinic in the late 90's, bringing them up from Access and Excel to an enterprise solution by degrees. After spending five years writing automated trading systems for the financial sector, he became a consultant on a variety of projects including the UI for a robotic warehouse, the middle tier for cancer research software, and the big data needs of a major real estate insurance company. In his free time he enjoys studying and writing about martial arts from the 16th century.



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