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  • Conditionally Auto-Executing af:query Search Form Based on User Input

    - by steve.muench
    Due to extreme lack of time due to other work priorities -- working hard on some interesting new ADF features for a future major release -- 2010 has not been a banner year for my production of samples to post to my blog, but to show my heart is in the right place I wanted to close out the year by posting example# 160: 160. Conditionally Auto-Executing af:query Search Form Based on User Input Enjoy. Happy New Year.

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  • SQL SERVER – Backing Up and Recovering the Tail End of a Transaction Log – Notes from the Field #042

    - by Pinal Dave
    [Notes from Pinal]: The biggest challenge which people face is not taking backup, but the biggest challenge is to restore a backup successfully. I have seen so many different examples where users have failed to restore their database because they made some mistake while they take backup and were not aware of the same. Tail Log backup was such an issue in earlier version of SQL Server but in the latest version of SQL Server, Microsoft team has fixed the confusion with additional information on the backup and restore screen itself. Now they have additional information, there are a few more people confused as they have no clue about this. Previously they did not find this as a issue and now they are finding tail log as a new learning. Linchpin People are database coaches and wellness experts for a data driven world. In this 42nd episode of the Notes from the Fields series database expert Tim Radney (partner at Linchpin People) explains in a very simple words, Backing Up and Recovering the Tail End of a Transaction Log. Many times when restoring a database over an existing database SQL Server will warn you about needing to make a tail end of the log backup. This might be your reminder that you have to choose to overwrite the database or could be your reminder that you are about to write over and lose any transactions since the last transaction log backup. You might be asking yourself “What is the tail end of the transaction log”. The tail end of the transaction log is simply any committed transactions that have occurred since the last transaction log backup. This is a very crucial part of a recovery strategy if you are lucky enough to be able to capture this part of the log. Most organizations have chosen to accept some amount of data loss. You might be shaking your head at this statement however if your organization is taking transaction logs backup every 15 minutes, then your potential risk of data loss is up to 15 minutes. Depending on the extent of the issue causing you to have to perform a restore, you may or may not have access to the transaction log (LDF) to be able to back up those vital transactions. For example, if the storage array or disk that holds your transaction log file becomes corrupt or damaged then you wouldn’t be able to recover the tail end of the log. If you do have access to the physical log file then you can still back up the tail end of the log. In 2013 I presented a session at the PASS Summit called “The Ultimate Tail Log Backup and Restore” and have been invited back this year to present it again. During this session I demonstrate how you can back up the tail end of the log even after the data file becomes corrupt. In my demonstration I set my database offline and then delete the data file (MDF). The database can’t become more corrupt than that. I attempt to bring the database back online to change the state to RECOVERY PENDING and then backup the tail end of the log. I can do this by specifying WITH NO_TRUNCATE. Using NO_TRUNCATE is equivalent to specifying both COPY_ONLY and CONTINUE_AFTER_ERROR. It as its name says, does not try to truncate the log. This is a great demo however how could I achieve backing up the tail end of the log if the failure destroys my entire instance of SQL and all I had was the LDF file? During my demonstration I also demonstrate that I can attach the log file to a database on another instance and then back up the tail end of the log. If I am performing proper backups then my most recent full, differential and log files should be on a server other than the one that crashed. I am able to achieve this task by creating new database with the same name as the failed database. I then set the database offline, delete my data file and overwrite the log with my good log file. I attempt to bring the database back online and then backup the log with NO_TRUNCATE just like in the first example. I encourage each of you to view my blog post and watch the video demonstration on how to perform these tasks. I really hope that none of you ever have to perform this in production, however it is a really good idea to know how to do this just in case. It really isn’t a matter of “IF” you will have to perform a restore of a production system but more of a “WHEN”. Being able to recover the tail end of the log in these sever cases could be the difference of having to notify all your business customers of data loss or not. If you want me to take a look at your server and its settings, or if your server is facing any issue we can Fix Your SQL Server. Note: Tim has also written an excellent book on SQL Backup and Recovery, a must have for everyone. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Improving 2D Range Query Performance in SQL Server

    When using the BETWEEN operator on multiple columns, you are likely using a 2D range query. Such queries perform very poorly in SQL Server. This article examines rewriting these queries for improved performance. Join SQL Backup’s 35,000+ customers to compress and strengthen your backups "SQL Backup will be a REAL boost to any DBA lucky enough to use it." Jonathan Allen. Download a free trial now.

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  • First steps on setting up a query based server [closed]

    - by asghar ashgari
    I got a physical server at home and I want to do the following silly project to learn the concept behind server-backend development, and then do a real project later on: Idea: Turn the server to a calculator. I want any person publicly send a query to the server (i.e., 2+2) from the terminal and the server give me the result. So the question is basically where to start, what sort of software I need to install, and what sort of program I need to write?.

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  • DAX Query Basics

    In this document I will attempt to talk you through writing your first very simple DAX queries. For the purpose of this document I will query the rather familiar Adventure Works Tabular Cube. Are you sure you can restore your backups? Run full restore + DBCC CHECKDB quickly and easily with SQL Backup Pro's new automated verification. Check for corruption and prepare for when disaster strikes. Try it now.

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  • NHibernate exception on query

    - by Yoav
    I'm getting a mapping exception doing the most basic query. This is my domain class: public class Project { public virtual string PK { get; set; } public virtual string Id { get; set; } public virtual string Name { get; set; } public virtual string Description { get; set; } } And the mapping class: public class ProjectMap :ClassMap<Project> { public ProjectMap() { Table("PROJECTS"); Id(x => x.PK, "PK"); Map(x => x.Id, "ID"); Map(x => x.Name, "NAME"); Map(x => x.Description, "DESCRIPTION"); } } Configuration: public ISessionFactory SessionFactory { return Fluently.Configure() .Database(MsSqlCeConfiguration.Standard.ShowSql().ConnectionString(c => c.Is("data source=" + path))) .Mappings(m => m.FluentMappings.AddFromAssemblyOf<Project>()) .BuildSessionFactory(); } And query: IList project; using (ISession session = SessionFactory.OpenSession()) { IQuery query = session.CreateQuery("from Project"); project = query.List<Project>(); } I'm getting the exception on the query line: NHibernate.Hql.Ast.ANTLR.QuerySyntaxException: Project is not mapped [from Project] at NHibernate.Hql.Ast.ANTLR.SessionFactoryHelperExtensions.RequireClassPersister(String name) at NHibernate.Hql.Ast.ANTLR.Tree.FromElementFactory.AddFromElement() at NHibernate.Hql.Ast.ANTLR.Tree.FromClause.AddFromElement(String path, IASTNode alias) at NHibernate.Hql.Ast.ANTLR.HqlSqlWalker.fromElement() at NHibernate.Hql.Ast.ANTLR.HqlSqlWalker.fromElementList() at NHibernate.Hql.Ast.ANTLR.HqlSqlWalker.fromClause() at NHibernate.Hql.Ast.ANTLR.HqlSqlWalker.unionedQuery() at NHibernate.Hql.Ast.ANTLR.HqlSqlWalker.query() at NHibernate.Hql.Ast.ANTLR.HqlSqlWalker.selectStatement() at NHibernate.Hql.Ast.ANTLR.HqlSqlWalker.statement() at NHibernate.Hql.Ast.ANTLR.HqlSqlTranslator.Translate() at NHibernate.Hql.Ast.ANTLR.QueryTranslatorImpl.Analyze(HqlParseEngine parser, String collectionRole) at NHibernate.Hql.Ast.ANTLR.QueryTranslatorImpl.DoCompile(IDictionary`2 replacements, Boolean shallow, String collectionRole) at NHibernate.Hql.Ast.ANTLR.QueryTranslatorImpl.Compile(IDictionary`2 replacements, Boolean shallow) at NHibernate.Engine.Query.HQLQueryPlan..ctor(String hql, String collectionRole, Boolean shallow, IDictionary`2 enabledFilters, ISessionFactoryImplementor factory) at NHibernate.Engine.Query.QueryPlanCache.GetHQLQueryPlan(String queryString, Boolean shallow, IDictionary`2 enabledFilters) at NHibernate.Impl.AbstractSessionImpl.GetHQLQueryPlan(String query, Boolean shallow) at NHibernate.Impl.AbstractSessionImpl.CreateQuery(String queryString) I assume something is wrong with my query.

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  • Translate Linq Expression to any existing Query structure?

    - by fredlegrain
    I have some kind of "data engine" between multiple "data consumer" processes and multiple "data storage" sources. I'd like to provide Linq capabilities to the "data consumer" and forward the query to the "data storage". The forwarded query should be some structured query (like, let's say, NHibernate Criteria). Is there any existing structured query library that could allow me to "just" translate a Linq Expression to such a structured query?

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  • error in fill datagrid whit query

    - by Amir Tavakoli
    i have a data-gride-view and i add my query to this when write my query i catch this error: The schema returned by the new query differs from the base query and this my query: SELECT B.SettingKey, 'SysSettingsDep' AS TableName, B.SettingValue, B.SettingDesc FROM SysCustomer AS A INNER JOIN SysSettingsDep AS B ON A.SettingKey = B.SettingKey UNION SELECT C.SettingKey, 'SysSettingsMachine' AS TableName, C.SettingValue, C.SettingDesc FROM SysCustomer AS A INNER JOIN SysSettingsMachine AS C ON A.SettingKey = C.SettingKey UNION SELECT D.SettingKey, 'SysSettings' AS TableName, D.SettingValue, D.SettingDesc FROM SysCustomer AS A INNER JOIN SysSettings AS D ON A.SettingKey = D.SettingKey help me to solve this, tnx

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  • Use textbox value on submit as a query string variable

    - by Eric
    How would I take a text box value and use it in the query string on submit? I'd like it to start as this, /News?favorites=True and end up something like this after the user enters in a search and clicks search. /News?query=test&favorites=True The controller action looks like this public ActionResult Index(string query,bool favorites) { //search code } This question is something close to what I'd like to do, but I'd like to use the query string and maintain the existing values in the query string. Thanks.

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  • DNS and name server in centos 6.3 64 bit is not pinged out side

    - by user135855
    I got a problem with centOS 6.3 64-bit. I want to setup my nameserver with bind here. I am listing all my configuration [root@izyon92 ~]# cat/etc/hosts -------------- 127.0.0.1 localhost localhost.localdomain localhost4 localhost4.localdomain4 ::1 localhost localhost.localdomain localhost6 localhost6.localdomain6 182.19.26.92 izyon92.zyonize1.com izyon92 [root@izyon92 ~]# cat /etc/sysconfig/network --------------------------------------------- NETWORKING=yes HOSTNAME=izyon92.zyonize1.com GATEWAY=182.19.26.89 [root@izyon92 ~]# cat /etc/resolv.conf -------------------------------------------- # Generated by NetworkManager search zyonize1.com nameserver 182.19.26.92 [root@izyon92 ~]# cat /etc/named.conf -------------------------------------------- // // named.conf // // Provided by Red Hat bind package to configure the ISC BIND named(8) DNS // server as a caching only nameserver (as a localhost DNS resolver only). // // See /usr/share/doc/bind*/sample/ for example named configuration files. // options { #listen-on port 53 { 127.0.0.1; }; listen-on-v6 port 53 { none; }; directory "/var/named"; dump-file "/var/named/data/cache_dump.db"; statistics-file "/var/named/data/named_stats.txt"; memstatistics-file "/var/named/data/named_mem_stats.txt"; allow-query { 182.19.26.92; }; recursion yes; dnssec-enable yes; dnssec-validation yes; dnssec-lookaside auto; /* Path to ISC DLV key */ bindkeys-file "/etc/named.iscdlv.key"; managed-keys-directory "/var/named/dynamic"; }; logging { channel default_debug { file "data/named.run"; severity dynamic; }; }; zone "." IN { type hint; file "named.ca"; }; include "/etc/named.rfc1912.zones"; include "/etc/named.root.key"; [root@izyon92 ~]# cat /etc/named.rfc1912.zones -------------------------------------------------- // named.rfc1912.zones: // // Provided by Red Hat caching-nameserver package // // ISC BIND named zone configuration for zones recommended by // RFC 1912 section 4.1 : localhost TLDs and address zones // and http://www.ietf.org/internet-drafts/draft-ietf-dnsop-default-local-zones-02.txt // (c)2007 R W Franks // // See /usr/share/doc/bind*/sample/ for example named configuration files. // zone "localhost.localdomain" IN { type master; file "named.localhost"; allow-update { none; }; }; zone "localhost" IN { type master; file "named.localhost"; allow-update { none; }; }; zone "1.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.ip6.arpa" IN { type master; file "named.loopback"; allow-update { none; }; }; zone "1.0.0.127.in-addr.arpa" IN { type master; file "named.loopback"; allow-update { none; }; }; zone "0.in-addr.arpa" IN { type master; file "named.empty"; allow-update { none; }; }; zone "zyonize1.com" { type master; file "/var/named/zyonize.com.hosts"; }; [root@izyon92 ~]# cat /var/named/zyonize.com.hosts --------------------------------------------------------- $ttl 38400 zyonize1.com. IN SOA 182.19.26.92. dev\.izyon.gmail.com. ( 1347436958 10800 3600 604800 38400 ) zyonize1.com. IN NS 182.19.26.92. zyonize1.com. IN A 182.19.26.92 www.zyonize1.com. IN A 182.19.26.92 izyon92.zyonize1.com. IN A 182.19.26.92 I have disabled selinux and stopped iptables. dig and nslookup is working fine in the same machine [root@izyon92 ~]# dig zyonize1.com ---------------------------------------- ; <<>> DiG 9.8.2rc1-RedHat-9.8.2-0.10.rc1.el6_3.2 <<>> zyonize1.com ;; global options: +cmd ;; Got answer: ;; ->>HEADER<<- opcode: QUERY, status: NOERROR, id: 55751 ;; flags: qr aa rd ra; QUERY: 1, ANSWER: 1, AUTHORITY: 1, ADDITIONAL: 0 ;; QUESTION SECTION: ;zyonize1.com. IN A ;; ANSWER SECTION: zyonize1.com. 38400 IN A 182.19.26.92 ;; AUTHORITY SECTION: zyonize1.com. 38400 IN NS 182.19.26.92. ;; Query time: 0 msec ;; SERVER: 182.19.26.92#53(182.19.26.92) ;; WHEN: Fri Sep 14 00:09:19 2012 ;; MSG SIZE rcvd: 72 [root@izyon92 ~]# nslookup zyonize1.com ---------------------------------------------- Server: 182.19.26.92 Address: 182.19.26.92#53 Name: zyonize1.com Address: 182.19.26.92 But here is the problem I am facing, I have windows machine, to test this dns and nameserver I set the first IPv4 DNS server to 182.19.26.92. Here is the details Connection-specific DNS Suffix: Description: Realtek PCIe GBE Family Controller Physical Address: ?14-FE-B5-9F-3A-A8 DHCP Enabled: No IPv4 Address: 192.168.2.50 IPv4 Subnet Mask: 255.255.255.0 IPv4 Default Gateway: 192.168.2.1 IPv4 DNS Servers: 182.19.26.92, 182.19.95.66 IPv4 WINS Server: NetBIOS over Tcpip Enabled: Yes Link-local IPv6 Address: fe80::45cc:2ada:c13:ca42%16 IPv6 Default Gateway: IPv6 DNS Server: when I am pining from this machine it is not finding the server. Where as in another server with another live IP with Fedora ping is working fine.

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  • WCF InProcFactory error

    - by Terence Lewis
    I'm using IDesign's ServiceModelEx assembly to provide additional functionality over and above what's available in standard WCF. In particular I'm making use of InProcFactory to host some WCF services within my process using Named Pipes. However, my process also declares a TCP endpoint in its configuration file, which I host and open when the process starts. At some later point, when I try to host a second instance of this service using the InProcFactory through the named pipe (from a different service in the same process), for some reason it picks up the TCP endpoint in the configuration file and tries to re-host this endpoint, which throws an exception as the TCP port is already in use from the first hosting. Here is the relevant code from InProcFactory.cs in ServiceModelEx: static HostRecord GetHostRecord<S,I>() where I : class where S : class,I { HostRecord hostRecord; if(m_Hosts.ContainsKey(typeof(S))) { hostRecord = m_Hosts[typeof(S)]; } else { ServiceHost<S> host; if(m_Singletons.ContainsKey(typeof(S))) { S singleton = m_Singletons[typeof(S)] as S; Debug.Assert(singleton != null); host = new ServiceHost<S>(singleton,BaseAddress); } else { host = new ServiceHost<S>(BaseAddress); } string address = BaseAddress.ToString() + Guid.NewGuid().ToString(); hostRecord = new HostRecord(host,address); m_Hosts.Add(typeof(S),hostRecord); host.AddServiceEndpoint(typeof(I),Binding,address); if(m_Throttles.ContainsKey(typeof(S))) { host.SetThrottle(m_Throttles[typeof(S)]); } // This line fails because it tries to open two endpoints, instead of just the named-pipe one host.Open(); } return hostRecord; }

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  • Versioned RDF store

    - by Mat
    Let me try rephrasing this: I am looking for a robust RDF store or library with the following features: Named graphs, or some other form of reification. Version tracking (probably at the named graph level). Privacy between groups of users, either at named graph or triple level. Human-readable data input and output, e.g. TriG parser and serialiser. I've played with Jena, Sesame, Boca, RDFLib, Redland and one or two others some time ago but each had its problems. Have any improved in the above areas recently? Can anything else do what I want, or is RDF not yet ready for prime-time? Reading around the subject a bit more, I've found that: Jena, nothing further Sesame, nothing further Boca does not appear to be maintained any more and seems only really designed for DB2. OpenAnzo, an open-source fork, appears more promising. RDFLib, nothing further Redland, nothing further Talis Platform appears to support changesets (wiki page and reference in Kniblet Tutorial Part 5) but it's a hosted-only service. Still may look into it though. SemVersion sounded promising, but appears to be stale.

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  • SQL SERVER – How to Recover SQL Database Data Deleted by Accident

    - by Pinal Dave
    In Repair a SQL Server database using a transaction log explorer, I showed how to use ApexSQL Log, a SQL Server transaction log viewer, to recover a SQL Server database after a disaster. In this blog, I’ll show you how to use another SQL Server disaster recovery tool from ApexSQL in a situation when data is accidentally deleted. You can download ApexSQL Recover here, install, and play along. With a good SQL Server disaster recovery strategy, data recovery is not a problem. You have a reliable full database backup with valid data, a full database backup and subsequent differential database backups, or a full database backup and a chain of transaction log backups. But not all situations are ideal. Here we’ll address some sub-optimal scenarios, where you can still successfully recover data. If you have only a full database backup This is the least optimal SQL Server disaster recovery strategy, as it doesn’t ensure minimal data loss. For example, data was deleted on Wednesday. Your last full database backup was created on Sunday, three days before the records were deleted. By using the full database backup created on Sunday, you will be able to recover SQL database records that existed in the table on Sunday. If there were any records inserted into the table on Monday or Tuesday, they will be lost forever. The same goes for records modified in this period. This method will not bring back modified records, only the old records that existed on Sunday. If you restore this full database backup, all your changes (intentional and accidental) will be lost and the database will be reverted to the state it had on Sunday. What you have to do is compare the records that were in the table on Sunday to the records on Wednesday, create a synchronization script, and execute it against the Wednesday database. If you have a full database backup followed by differential database backups Let’s say the situation is the same as in the example above, only you create a differential database backup every night. Use the full database backup created on Sunday, and the last differential database backup (created on Tuesday). In this scenario, you will lose only the data inserted and updated after the differential backup created on Tuesday. If you have a full database backup and a chain of transaction log backups This is the SQL Server disaster recovery strategy that provides minimal data loss. With a full chain of transaction logs, you can recover the SQL database to an exact point in time. To provide optimal results, you have to know exactly when the records were deleted, because restoring to a later point will not bring back the records. This method requires restoring the full database backup first. If you have any differential log backup created after the last full database backup, restore the most recent one. Then, restore transaction log backups, one by one, it the order they were created starting with the first created after the restored differential database backup. Now, the table will be in the state before the records were deleted. You have to identify the deleted records, script them and run the script against the original database. Although this method is reliable, it is time-consuming and requires a lot of space on disk. How to easily recover deleted records? The following solution enables you to recover SQL database records even if you have no full or differential database backups and no transaction log backups. To understand how ApexSQL Recover works, I’ll explain what happens when table data is deleted. Table data is stored in data pages. When you delete table records, they are not immediately deleted from the data pages, but marked to be overwritten by new records. Such records are not shown as existing anymore, but ApexSQL Recover can read them and create undo script for them. How long will deleted records stay in the MDF file? It depends on many factors, as time passes it’s less likely that the records will not be overwritten. The more transactions occur after the deletion, the more chances the records will be overwritten and permanently lost. Therefore, it’s recommended to create a copy of the database MDF and LDF files immediately (if you cannot take your database offline until the issue is solved) and run ApexSQL Recover on them. Note that a full database backup will not help here, as the records marked for overwriting are not included in the backup. First, I’ll delete some records from the Person.EmailAddress table in the AdventureWorks database.   I can delete these records in SQL Server Management Studio, or execute a script such as DELETE FROM Person.EmailAddress WHERE BusinessEntityID BETWEEN 70 AND 80 Then, I’ll start ApexSQL Recover and select From DELETE operation in the Recovery tab.   In the Select the database to recover step, first select the SQL Server instance. If it’s not shown in the drop-down list, click the Server icon right to the Server drop-down list and browse for the SQL Server instance, or type the instance name manually. Specify the authentication type and select the database in the Database drop-down list.   In the next step, you’re prompted to add additional data sources. As this can be a tricky step, especially for new users, ApexSQL Recover offers help via the Help me decide option.   The Help me decide option guides you through a series of questions about the database transaction log and advises what files to add. If you know that you have no transaction log backups or detached transaction logs, or the online transaction log file has been truncated after the data was deleted, select No additional transaction logs are available. If you know that you have transaction log backups that contain the delete transactions you want to recover, click Add transaction logs. The online transaction log is listed and selected automatically.   Click Add if to add transaction log backups. It would be best if you have a full transaction log chain, as explained above. The next step for this option is to specify the time range.   Selecting a small time range for the time of deletion will create the recovery script just for the accidentally deleted records. A wide time range might script the records deleted on purpose, and you don’t want that. If needed, you can check the script generated and manually remove such records. After that, for all data sources options, the next step is to select the tables. Be careful here, if you deleted some data from other tables on purpose, and don’t want to recover them, don’t select all tables, as ApexSQL Recover will create the INSERT script for them too.   The next step offers two options: to create a recovery script that will insert the deleted records back into the Person.EmailAddress table, or to create a new database, create the Person.EmailAddress table in it, and insert the deleted records. I’ll select the first one.   The recovery process is completed and 11 records are found and scripted, as expected.   To see the script, click View script. ApexSQL Recover has its own script editor, where you can review, modify, and execute the recovery script. The insert into statements look like: INSERT INTO Person.EmailAddress( BusinessEntityID, EmailAddressID, EmailAddress, rowguid, ModifiedDate) VALUES( 70, 70, N'[email protected]' COLLATE SQL_Latin1_General_CP1_CI_AS, 'd62c5b4e-c91f-403f-b630-7b7e0fda70ce', '20030109 00:00:00.000' ); To execute the script, click Execute in the menu.   If you want to check whether the records are really back, execute SELECT * FROM Person.EmailAddress WHERE BusinessEntityID BETWEEN 70 AND 80 As shown, ApexSQL Recover recovers SQL database data after accidental deletes even without the database backup that contains the deleted data and relevant transaction log backups. ApexSQL Recover reads the deleted data from the database data file, so this method can be used even for databases in the Simple recovery model. Besides recovering SQL database records from a DELETE statement, ApexSQL Recover can help when the records are lost due to a DROP TABLE, or TRUNCATE statement, as well as repair a corrupted MDF file that cannot be attached to as SQL Server instance. You can find more information about how to recover SQL database lost data and repair a SQL Server database on ApexSQL Solution center. There are solutions for various situations when data needs to be recovered. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQLAuthority News – Pluralsight Course Review – Practices for Software Startups – Part 1 of 2

    - by pinaldave
    This is first part of the two part series of Practices for Software Startup Pluralsight Course. The course is written by Stephen Forte (Blog | Twitter). Stephen Forte is the Chief Strategy Officer of the venture backed company, Telerik, a leading vendor of developer and team productivity tools. Stephen is also a Certified Scrum Master, Certified Scrum Professional, PMP, and also speaks regularly at industry conferences around the world. He has written several books on application and database development.  Stephen is also a board member of the Scrum Alliance. Startups – Everybodies Dream Start-up companies are an important topic right now – everyone wants to start their own business.  It is also important to remember that all companies were a start up at one point – from your corner store to the giants like Microsoft and Apple.  Research proves that not every start-up succeeds, in fact, most will fail before their first year.  There are many reasons for this, and this could be due to the fact that there are many stages to a start-up company, and stumbling at any of these stages can lead to failure.  It is important to understand what makes a start-up company succeed at all its hurdles to become successful.  It is even important to define success.  For most start-ups this would mean becoming their own independently functioning company or to be bought out for a hefty profit by a larger company.  The idea of making a hefty profit by living your dream is extremely important, and you can even think of start-ups as the new craze.  That’s why studying them is so important – they are very popular, but things have changed a lot since their inception. Starting the Startups Beginning a start-up company used to be difficult, but now facilities and information is widely available, and it is much easier.  But that means it is much easier to fail, also.  Previously to start your own company, everything was planned and organized, resources were ensured and backed up before beginning; even the idea of starting your own business was a big thing.  Now anybody can do it, and the steps are simple and outlines everywhere – you can get online software and easily outsource , cloud source, or crowdsource a lot of your material.  But without the type of planning previously required, things can often go badly. New Products – New Ideas – New World There are so many fantastic new products, but they don’t reach success all the time.  I find start-up companies very interesting, and whenever I meet someone who is interested in the subject or already starting their own company, I always ask what they are doing, their plans, goals, market, etc.  I am sorry to say that in most cases, they cannot answer my questions.  It is true that many fantastic ideas fail because of bad decisions.  These bad decisions were not made intentionally, but people were simply unaware of what they should be doing.  This will always lead to failure.  But I am happy to say that all these issues can be gone because Pluralsight is now offering a course all about start-ups by Stephen Forte.  Stephen is a start up leader.  He has successfully started many companies and most are still going strong, or have gone on to even bigger and better things. Beginning Course on Startup I have always thought start-ups are a fascinating subject, and decided to take his course, but it is three hours long.  This would be hard to fit into my busy work day all at once, so I decided to do half of his course before my daughter wakes up, and the other half after she goes to sleep.  The course is divided into six modules, so this would be easy to do.  I began the first chapter early in the morning, at 5 am.  Stephen jumped right into the middle of the subject in the very first module – designing your business plan.  The first question you will have to answer to yourself, to others, and to investors is: What is your product and when will we be able to see it?  So a very important concept is a “minimal viable product.”  This means setting goals for yourself and your product.  We all have large dreams, but your minimal viable product doesn’t have to be your final vision at the very first.  For example: Apple is a giant company, but it is still evolving.  Steve Jobs didn’t envision the iPhone 6 at the very beginning.  He had to start at the first iPhone and do his market research, and the idea evolved into the technology you see now.  So for yourself, you should decide a beginning and stop point.  Do your market research.  Determine who you want to reach, what audience you want for your product.  You can have a great idea that simply will not work in the market, do need, bottlenecks, lack of resources, or competition.  There is a lot of research that needs to be done before you even write a business plan, and Stephen covers it in the very first chapter. The Team – Unique Key to Success After jumping right into the subject in the very first module, I wondered what Stephen could have in store for me for the rest of the course.  Chapter number two is building a team.  Having a team is important regardless of what your startup is.  You can be a true visionary with endless ideas and energy, but one person can still not do everything.  It is important to decide from the very beginning if you will have cofounders, team leaders, and how many employees you’ll need.  Even more important, you’ll need to decide what kind of team you want – what personalities, skills, and type of energy you want each of your employees to bring.  Do you want to have an A+ team with a B- idea, or do you have a B- idea that needs an A+ team to sell it?  Stephen asks all the hard questions!  I was especially impressed by his insight on developing.  You have to decide if you need developers, how many, and what their skills should be. I found this insight extremely useful for everyday usage, not just for start-up companies.  I would apply this kind of information in management at any position.  An amazing team will build an amazing product – and that doesn’t matter if you’re a start-up company or a small team working for a much larger business. Customer Development – The Ultimate Obective Chapter three was about customer development. According to Stephen, there are four different steps to develop a customer base.  The first question to ask yourself is if you are envisioning a large customer base buying a few products each, or a small, dedicated base that buys a lot of your product – quantity vs. Quality.  He also discusses how to earn, retain, and get more customers.  He also says that each customer should be placed in a different role – some will be like investors, who regularly spend with you and invest their money in your business.  It is then your job to take that investment and turn it into a better product in the future.  You need to deal with their money properly – think of it is as theirs as investors, not yours as profit.  At the end of this module I felt that only Stephen could provide this kind of insight, and then he listed all the resources he took his information from.  I have never seen a group of people so passionate about their customers. It was indeed a long day for me. In tomorrow’s part 2 we will discuss rest of the three module and also will see a quick video of the Practices for Software Startup Pluralsight Course. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Best Practices, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQLAuthority News – Memories at Anniversary of SQL Wait Stats Book

    - by pinaldave
    SQL Wait Stats About a year ago, I had very proud moment. I had published my second book SQL Server Wait Stats with me as a primary author. It has been a long journey since then. The book got great response and it was widely accepted in the community. It was first of its kind of book written specifically on Wait Stats and Performance. The book was based on my earlier month long series written on the same subject SQL Server Wait Stats. Today, on the anniversary of the book, lots of things come to my mind let me share a few here. Idea behind Blog Series A very common question I often receive is why I wrote a 30 day series on Wait Stats. There were two reasons for it. 1) I have been working with SQL Server for a long time and have troubleshoot more than hundreds of SQL Server which are related to performance tuning. It was a great experience and it taught me a lot of new things. I always documented my experience. After a while I found that I was able to completely rely on my own notes when I was troubleshooting any servers. It is right then I decided to document my experience for the community. 2) While working with wait stats there were a few things, which I thought I knew it well as they were working. However, there was always a fear in the back of mind that what happens if what I believed was incorrect and I was on the wrong path all the time. There was only one way to get it validated. Put it out in front community with my understanding and request further help to improve my understanding. It worked, it worked beautifully. I received plenty of conversations, emails and comments. I refined my content based on various conversations and make it more relevant and near accurate. I guess above two are the major reasons for beginning my journey on writing Wait Stats blog series. Idea behind Book After writing a blog series there was a good amount of request I keep on receiving that I should convert it to eBook or proper book as reading blog posts is great but it goes not give a comprehensive understanding of the subject. The very common feedback from users who were beginning the subject that they will prefer to read it in a structured method. After hearing the feedback for more than 4 months, I decided to write a book based on the blog posts. When I envisioned book, I wanted to make sure this book addresses the wait stats concepts from the fundamentals and fill the gaps of blogs I wrote earlier. Rick Morelan and Joes 2 Pros Team I must acknowledge my co-author Rick Morelan for his unconditional support in writing this book. I had already authored one book before I published this book. The experience to write the book was out of the world. Writing blog posts are much much easier than writing books. The efforts it takes to write a book is 100 times more even though the content is ready. I could have not done it myself if there was not tremendous support of my co-author and editor’s team. We spend days and days researching and discussing various concepts covered in the book. When we were in doubt we reached out to experts as well did a practical reproduction of the scenarios to validate the concepts and claims. After continuous 3 months of hard work we were able to get this book out in the community. September 1st – the lucky day Well, we had to select any day to publish the books. When book was completed in August last week we felt very glad. We all had worked hard and having a sample draft book in hand was feeling like having a newborn baby in our hand. Every time my books are published I feel the same joy which I had when my daughter was born. The feeling of holding a new book in hand is the (almost) same feeling as holding newborn baby. I am excited. For me September 1st has been the luckiest day in mind life. My daughter Shaivi was born on September 1st. Since then every September first has been excellent day and have taken me to the next step in life. I believe anything and everything I do on September 1st it is turning out to be successful and blessed. Rick and I had finished a book in the last week of August. We sent it to the publisher (printer) and asked him to take the book live as soon as possible. We did not decide on any date as we wanted the book to get out as fast as it can. Interesting enough, the publisher/printer selected September 1st for publishing the book. He published the book on 1st September and I knew it at the same time that this book will go next level. Book Model – The Most Beautiful Girl We were done with book. We had no budget left for marketing. Rick and I had a long conversation regarding how to spread the words for the book so it can reach to many people. While we were talking about marketing Rick come up with the idea that we should hire a most beautiful girl around who acknowledge our book and genuinely care for book. It was a difficult task and Rick asked me to find a more beautiful girl. I am a father and the most beautiful girl for me my daughter. This was not a difficult task for me. Rick had given me task to find the most beautiful girl and I just could not think of anyone else than my own daughter. I still do not know what Rick thought about this idea but I had already made up my mind. You can see the detailed blog post here. The Fun Experiments Book Signing Event We had lots of fun moments along this book. We have given away more books to people for free than we have sold them actually. We had done book signing events, contests, and just plain give away when we found people can be benefited from this book. There was never an intention to make money and get rich. We just wanted that more and more people know about this new concept and learn from it. Today when I look back to the earnings there is nothing much we have earned if you talk about dollars. However the best reward which we have received is the satisfaction and love of community. The amount of emails, conversations we have so far received for this book is over thousands. We had fun writing this book, it was indeed a very satisfying journey. I have earned lots of friends while learning and exploring. Availability The book is one year old but still very relevant when it is about performance tuning. It is available at various online book stores. If you have read the book, do let me know what you think of it. Amazon | Kindle | Flipkart | Indiaplaza Reference:  Pinal Dave (http://blog.SQLAuthority.com) Filed under: About Me, Joes 2 Pros, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority, SQLAuthority Book Review, T SQL, Technology

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  • SQLAuthority Book Review – DBA Survivor: Become a Rock Star DBA

    - by pinaldave
    DBA Survivor: Become a Rock Star DBA – Thomas LaRock Link to Amazon Link to Flipkart First of all, I thank all my readers when I wrote that I could not get this book in any local book stores, because they offered me to send a copy of this good book. A very special mention goes to Sripada and Jayesh for they gave so much effort in finding my home address and sending me the hard copy. Before, I did not have the copy of the book, but now I have two of it already! It surprises me how my readers were able to find my home address, which I have not publicly shared. Quick Review: This is indeed a one easy-to-read and fun book. We all work day and night with technology yet we should not forget to show our love and care for our family at home. For our souls that starve for peace and guidance, this one book is the “it” book for all the technology enthusiasts. Though this book was specifically written for DBAs, the reach is not limited to DBAs only because the lessons incorporated in it actually applies to all. This is one of the most motivating technical books I have read. Detailed Review: Let us go over a few questions first: Who wants to be as famous as rockstars in the field of Database Administration? How can one learn what it takes to become a top notch software developer? If you are a beginner in your field, how will you go to next level? Your boss may be very kind or like Dilbert’s Boss, what will you do? How do you keep growing when Eco-system around you does not support you? You are almost at top but there is someone else at the TOP, what do you do and how do you avoid office politics? As a database developer what should be your basic responsibility? and many more… I was able to completely read book in one sitting and I loved it. Before I continue with my opinion, I want to echo the opinion of Kevin Kline who has written the Forward of the book. He has truly suggested that “You hold in your hands a collection of insights and wisdom on the topic of database administration gained through many years of hard-won experience, long nights of study, and direct mentorship under some of the industry’s most talented database professionals and information technology (IT) experts.” Today, IT field is getting bigger and better, while talking about terabytes of the database becomes “more” normal every single day. The gods and demigods of database professionals are taking care of these large scale databases and are carefully maintaining them. In this world, there are only a few beginnings on the first step. There are many experts in different technology fields who are asked to address the issues with databases. There is YOU and ME, who is just new to this work. So we ask ourselves WHERE to begin and HOW to begin. We adore and follow the religion of our rockstars, but oftentimes we really have no idea about their background and their struggles. Every rockstar has his success story which needs to be digested before learning his tricks and tips. This book starts with the same note and teaches the two most important lessons for anybody who wants to be a DBA Rockstar –  to focus on their single goal of learning and to excel the technology. The story starts with three simple guidelines – Get Prepared, Get Trained, Get Certified. Once a person learns the skills, and then, it would be about time that he needs to enrich or to improve those skills you have learned. I am sure that the right opportunity will come finding themselves and they will not have to go run behind it. However, the real challenge for any person is the first day or first week. A new employee, no matter how much experienced he is, sometimes has no clue about what should one do at new job. Chapter 2 and chapter 3 precisely talk about what one should do as soon as the new job begins. It is also written with keeping the fact in focus that each job can be very much different but there are few infrastructure setups and programming concepts are the same. Learning basics of database was really interesting. I like to focus on the roots of any technology. It is important to understand the structure of the database before suggesting what indexes needs to be created, the same way this book covers the most essential knowledge one must learn by most database developers. I think the title of the fourth chapter is my favorite sentence in this book. I can see that I will be saying this again and again in the future – “A Development Server Is a Production Server to a Developer“. I have worked in the software industry for almost 8 years now and I have seen so many developers sitting on their chairs and waiting for instructions from their lead about how to improve the code or what to do the next. When I talk to them, I suggest that the experiment with their server and try various techniques. I think they all should understand that for them, a development server is their production server and needs to pay proper attention to the code from the beginning. There should be NO any inappropriate code from the beginning. One has to fully focus and give their best, if they are not sure they should ask but should do something and stay active. Chapter 5 and 6 talks about two essential skills for any developer and database administration – what are the ethics of developers when they are working with production server and how to support software which is running on the production server. I have met many people who know the theory by heart but when put in front of keyboard they do not know where to start. The first thing they do opening the browser and searching online, instead of opening SQL Server Management Studio. This can very well happen to anybody who is experienced as well. Chapter 5 and 6 addresses that situation as well includes the handy scripts which can solve almost all the basic trouble shooting issues. “Where’s the Buffet?” By far, this is the best chapter in this book. If you have ever met me, you would know that I love food. I think after reading this chapter, I felt Thomas has written this just keeping me in mind. I think there will be many other people who feel the same way, too. Even my wife who read this chapter thought this was specifically written for me. I will not talk any more about this chapter as this is one must read chapter. And of course this is about real ‘FOOD‘. I am an SQL Server Trainer and Consultant and I totally agree with the point made in the chapter 8 of this book. Yes, it says here that what is necessary to train employees and people. Millions of dollars worth the labor is continuously done in the world which has faults and incorrect. Once something goes wrong, very expensive consultant comes in and fixes the problem. This whole cycle which can be stopped and improved if proper training is done. There is plenty of free trainings available as well, if one cannot afford paid training. “Connect. Learn. Share” – I think this is a great summary and bird’s eye view of this book. Networking is the key. Everything which is discussed in this book can be taken to next level if one properly uses this tips and continuously grow with it. Connecting with others, helping learn each other and building the good knowledge sharing environment should be the goal of everyone. Before I end the review I want to share a real experience. I have personally met one DBA who has worked in a single department in a company for so long that when he was put in a different department in his company due to closing that department, he could not adjust and quit the job despite the same people and company around him. Adjusting in the new environment gets much tougher as one person gets more and more experienced. This book precisely addresses the same issue along with their solutions. I just cannot stop comparing the book with my personal journey. I found so many things which are coincidently in the book is written as how we developer and DBA think. I must express special thanks to Thomas for taking time in his personal life and write this book for us. This book is indeed a book for everybody who wants to grow healthy in the tough and competitive environment. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Book Review, SQLAuthority News, SQLServer, T SQL, Technology

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  • SQLAuthority News – Pluralsight Course Review – Practices for Software Startups – Part 2 of 2

    - by pinaldave
    This is the second part of the two part series of Practices for Software Startup Pluralsight Course. Please read the first part of this series over here. The course is written by Stephen Forte (Blog | Twitter). Stephen Forte is the Chief Strategy Officer of the venture backed company, Telerik. Personal Learning Schedule After these three sessions it was 6:30 am and time to do my own blog.  But for the rest of the day, I kept thinking about the course, and wanted to go back and finish.  I was wishing that I had woken up at 3 am so I could finish all at one go.  All day long I was digesting what I had learned.  At 10 pm, after my daughter had gone to bed, I sighed on again.  I was not disappointed by the long wait.  As I mentioned before, Stephen has started four to six companies, and all of them are very successful today. Here is the video I promised yesterday – it discusses the importance of Right Sizing Your Startup. The Heartbeat of Startup – Technology Stephen has combined all technology knowledge into one 30 minute session.  He discussed  how to start your project, how to deal with opinions, and how to deal with multiple ideas – every start up has multiple directions it can go. He spent a lot of time emphasized deciding which direction to go and how to decide which will be the best for you.  He called it a continuous development cycle. One of the biggest hazards for a start-up company is one person deciding the direction the company will go, until down the road another team member announces that there is a glitch in their part of the work and that everyone will have to start over.  Even though a team of two or five people can move quickly, often the decision has gone too long and cannot be easily fixed.   Stephen used an example from his own life:  he was biased for one type of technology, and his teammate for another.  In the end they opted for his teammate’s  choice , and in the end it was a good decision, even though he was unfamiliar with that particular program.  He argues that technology should not be a barrier to progress, that you cannot rely on your experience only.  This really spoke to me because I am a big fan of SQL, but I know there is more out there, and I should be more open to it.  I give my thanks to Stephen, I learned something in this module besides startups. Money, Success and Epic Win! The longest, but most interesting, the module was funding your start-up.  You need to fund the start-up right at the very beginning, if not done right you will run into trouble.  The good news is that a few years ago start-ups required a lot more money – think millions of dollars – but now start-ups can get off the ground for thousands.  Stephen used an example of a company that years ago would have needed a million dollars, but today could be started for $600.  It is true that things have changed, but you still need money.  For $600 you can start small and add dynamically, as needed.  But the truth is that if you have $600, $6000, or $6 million, it will be spent.  Don’t think of it as trying to save money, think of it as investing in your future.   You will need money, and you will need to (quickly) decide what you do with the money: shares, stakeholders, investing in a team, hiring a CEO.  This is so important because once you have money and start the company, the company IS your money.  It is your biggest currency – having a percentage of ownership in the company.  Investors will want percentages as repayment for their investment, and they will want a say in the business as well.  You will have to decide how far you will dilute your shares, and how the company will be divided, if at all.  If you don’t plan in advance, you will find that after gaining three or four investors, suddenly you are the minority owner in your own dream.  You need to understand funding carefully.  This single module is worth all the money you would have spent on the whole course alone.  I encourage everyone to listen to this single module even if they don’t watch any of the others.     Press End to Start the Game – Exists! The final module is exit strategies.  You did all this work, dealt with all political and legal issues.  What are you going to get out of it? The answer is simple: money.  Maybe you want your company to be bought out, for you talent to bring you a profit.  You can sell the company to someone and still head it.  Many options are available.  You could sell and still work as an employee but no longer own the company.  There are many exit strategies.  This is where all your hard work comes into play.  It is important not to feel fooled at any step.  There are so many good ideas that end up in the garbage because of poor planning, so that if you find yourself successful, you don’t want to blow it at this step!  The exit is important.  I thought that this aspect of the course was completely unique, and I loved Stephen’s point of view.  I was lost deep in thought after this module ended.  I actually took two hours worth of notes on this section alone – and it was only a three hour course.  I am planning on attending this course one more time next week, just to catch up on all the small bits of wisdom I’m sure I missed. Thank you Stephen for bringing your real world experience with us!  I recommend that everyone attends this course, even if they don’t want to begin their own start-up company. It was indeed a long day for me. Do not forget to read part 1 of this story and attend course Practices for Software Startup Pluralsight Course. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Best Practices, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – Interview Questions and Answers – Frequently Asked Questions – Introduction – Day 1 of 31

    - by pinaldave
    List of all the Interview Questions and Answers Series blogs Posts covering interview questions and answers always make for interesting reading.  Some people like the subject for their helpful hints and thought provoking subject, and others dislike these posts because they feel it is nothing more than cheating.  I’d like to discuss the pros and cons of a Question and Answer format here. Interview Questions and Answers are Helpful Just like blog posts, books, and articles, interview Question and Answer discussions are learning material.  The popular Dummy’s books or Idiots Guides are not only for “dummies,” but can help everyone relearn the fundamentals.  Question and Answer discussions can serve the same purpose.  You could call this SQL Server Fundamentals or SQL Server 101. I have administrated hundreds of interviews during my career and I have noticed that sometimes an interviewee with several years of experience lacks an understanding of the fundamentals.  These individuals have been in the industry for so long, usually working on a very specific project, that the ABCs of the business have slipped their mind. Or, when a college graduate is looking to get into the industry, he is not expected to have experience since he is just graduated. However, the new grad is expected to have an understanding of fundamentals and theory.  Sometimes after the stress of final exams and graduation, it can be difficult to remember the correct answers to interview questions, though. An interview Question and Answer discussion can be very helpful to both these individuals.  It is simply a way to go back over the building blocks of a topic.  Many times a simple review like this will help “jog” your memory, and all those previously-memorized facts will come flooding back to you.  It is not a way to re-learn a topic, but a way to remind yourself of what you already know. A Question and Answer discussion can also be a way to go over old topics in a more interesting manner.  Especially if you have been working in the industry, or taking lots of classes on the topic, everything you read can sound like a repeat of what you already know.  Going over a topic in a new format can make the material seem fresh and interesting.  And an interested mind will be more engaged and remember more in the end. Interview Questions and Answers are Harmful A common argument against a Question and Answer discussion is that it will give someone a “cheat sheet.” A new guy with relatively little experience can read the interview questions and answers, and then memorize them. When an interviewer asks him the same questions, he will repeat the answers and get the job. Honestly, is he good hire because he memorized the interview questions? Wouldn’t it be better for the interviewer to hire someone with actual experience?  The answer is not as easy as it seems – there are many different factors to be considered. If the interviewer is asking fundamentals-related questions only, he gets the answers he wants to hear, and then hires this first candidate – there is a good chance that he is hiring based on personality rather than experience.  If the interviewer is smart he will ask deeper questions, have more than one person on the interview team, and interview a variety of candidates.  If one interviewee happens to memorize some answers, it usually doesn’t mean he will automatically get the job at the expense of more qualified candidates. Another argument against interview Question and Answers is that it will give candidates a false sense of confidence, and that they will appear more qualified than they are. Well, if that is true, it will not last after the first interview when the candidate is asked difficult questions and he cannot find the answers in the list of interview Questions and Answers.  Besides, confidence is one of the best things to walk into an interview with! In today’s competitive job market, there are often hundreds of candidates applying for the same position.  With so many applicants to choose from, interviewers must make decisions about who to call back and who to hire based on their gut feeling.  One drawback to reading an interview Question and Answer article is that you might sound very boring in your interview – saying the same thing as every single candidate, and parroting answers that sound like someone else wrote them for you – because they did.  However, it is definitely better to go to an interview prepared, just make sure that you give a lot of thought to your answers to make them sound like your own voice.  Remember that you will be hired based on your skills as well as your personality, so don’t think that having all the right answers will make get you hired.  A good interviewee will be prepared, confident, and know how to stand out. My Opinion A list of interview Questions and Answers is really helpful as a refresher or for beginners. To really ace an interview, one needs to have real-world, hands-on experience with SQL Server as well. Interview questions just serve as a starter or easy read for experienced professionals. When I have to learn new technology, I often search online for interview questions and get an idea about the breadth and depth of the technology. Next Action I am going to write about interview Questions and Answers for next 30 days. I have previously written a series of interview questions and answers; now I have re-written them keeping the latest version of SQL Server and current industry progress in mind. If you have faced interesting interview questions or situations, please write to me and I will publish them as a guest post. If you want me to add few more details, leave a comment and I will make sure that I do my best to accommodate. Tomorrow we will start the interview Questions and Answers series, with a few interesting stories, best practices and guest posts. We will have a prize give-away and other awards when the series ends. List of all the Interview Questions and Answers Series blogs Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Interview Questions and Answers, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Big Data – Is Big Data Relevant to me? – Big Data Questionnaires – Guest Post by Vinod Kumar

    - by Pinal Dave
    This guest post is by Vinod Kumar. Vinod Kumar has worked with SQL Server extensively since joining the industry over a decade ago. Working on various versions of SQL Server 7.0, Oracle 7.3 and other database technologies – he now works with the Microsoft Technology Center (MTC) as a Technology Architect. Let us read the blog post in Vinod’s own voice. I think the series from Pinal is a good one for anyone planning to start on Big Data journey from the basics. In my daily customer interactions this buzz of “Big Data” always comes up, I react generally saying – “Sir, do you really have a ‘Big Data’ problem or do you have a big Data problem?” Generally, there is a silence in the air when I ask this question. Data is everywhere in organizations – be it big data, small data, all data and for few it is bad data which is same as no data :). Wow, don’t discount me as someone who opposes “Big Data”, I am a big supporter as much as I am a critic of the abuse of this term by the people. In this post, I wanted to let my mind flow so that you can also think in the direction I want you to see these concepts. In any case, this is not an exhaustive dump of what is in my mind – but you will surely get the drift how I am going to question Big Data terms from customers!!! Is Big Data Relevant to me? Many of my customers talk to me like blank whiteboard with no idea – “why Big Data”. They want to jump into the bandwagon of technology and they want to decipher insights from their unexplored data a.k.a. unstructured data with structured data. So what are these industry scenario’s that come to mind? Here are some of them: Financials Fraud detection: Banks and Credit cards are monitoring your spending habits on real-time basis. Customer Segmentation: applies in every industry from Banking to Retail to Aviation to Utility and others where they deal with end customer who consume their products and services. Customer Sentiment Analysis: Responding to negative brand perception on social or amplify the positive perception. Sales and Marketing Campaign: Understand the impact and get closer to customer delight. Call Center Analysis: attempt to take unstructured voice recordings and analyze them for content and sentiment. Medical Reduce Re-admissions: How to build a proactive follow-up engagements with patients. Patient Monitoring: How to track Inpatient, Out-Patient, Emergency Visits, Intensive Care Units etc. Preventive Care: Disease identification and Risk stratification is a very crucial business function for medical. Claims fraud detection: There is no precise dollars that one can put here, but this is a big thing for the medical field. Retail Customer Sentiment Analysis, Customer Care Centers, Campaign Management. Supply Chain Analysis: Every sensors and RFID data can be tracked for warehouse space optimization. Location based marketing: Based on where a check-in happens retail stores can be optimize their marketing. Telecom Price optimization and Plans, Finding Customer churn, Customer loyalty programs Call Detail Record (CDR) Analysis, Network optimizations, User Location analysis Customer Behavior Analysis Insurance Fraud Detection & Analysis, Pricing based on customer Sentiment Analysis, Loyalty Management Agents Analysis, Customer Value Management This list can go on to other areas like Utility, Manufacturing, Travel, ITES etc. So as you can see, there are obviously interesting use cases for each of these industry verticals. These are just representative list. Where to start? A lot of times I try to quiz customers on a number of dimensions before starting a Big Data conversation. Are you getting the data you need the way you want it and in a timely manner? Can you get in and analyze the data you need? How quickly is IT to respond to your BI Requests? How easily can you get at the data that you need to run your business/department/project? How are you currently measuring your business? Can you get the data you need to react WITHIN THE QUARTER to impact behaviors to meet your numbers or is it always “rear-view mirror?” How are you measuring: The Brand Customer Sentiment Your Competition Your Pricing Your performance Supply Chain Efficiencies Predictive product / service positioning What are your key challenges of driving collaboration across your global business?  What the challenges in innovation? What challenges are you facing in getting more information out of your data? Note: Garbage-in is Garbage-out. Hold good for all reporting / analytics requirements Big Data POCs? A number of customers get into the realm of setting a small team to work on Big Data – well it is a great start from an understanding point of view, but I tend to ask a number of other questions to such customers. Some of these common questions are: To what degree is your advanced analytics (natural language processing, sentiment analysis, predictive analytics and classification) paired with your Big Data’s efforts? Do you have dedicated resources exploring the possibilities of advanced analytics in Big Data for your business line? Do you plan to employ machine learning technology while doing Advanced Analytics? How is Social Media being monitored in your organization? What is your ability to scale in terms of storage and processing power? Do you have a system in place to sort incoming data in near real time by potential value, data quality, and use frequency? Do you use event-driven architecture to manage incoming data? Do you have specialized data services that can accommodate different formats, security, and the management requirements of multiple data sources? Is your organization currently using or considering in-memory analytics? To what degree are you able to correlate data from your Big Data infrastructure with that from your enterprise data warehouse? Have you extended the role of Data Stewards to include ownership of big data components? Do you prioritize data quality based on the source system (that is Facebook/Twitter data has lower quality thresholds than radio frequency identification (RFID) for a tracking system)? Do your retention policies consider the different legal responsibilities for storing Big Data for a specific amount of time? Do Data Scientists work in close collaboration with Data Stewards to ensure data quality? How is access to attributes of Big Data being given out in the organization? Are roles related to Big Data (Advanced Analyst, Data Scientist) clearly defined? How involved is risk management in the Big Data governance process? Is there a set of documented policies regarding Big Data governance? Is there an enforcement mechanism or approach to ensure that policies are followed? Who is the key sponsor for your Big Data governance program? (The CIO is best) Do you have defined policies surrounding the use of social media data for potential employees and customers, as well as the use of customer Geo-location data? How accessible are complex analytic routines to your user base? What is the level of involvement with outside vendors and third parties in regard to the planning and execution of Big Data projects? What programming technologies are utilized by your data warehouse/BI staff when working with Big Data? These are some of the important questions I ask each customer who is actively evaluating Big Data trends for their organizations. These questions give you a sense of direction where to start, what to use, how to secure, how to analyze and more. Sign off Any Big data is analysis is incomplete without a compelling story. The best way to understand this is to watch Hans Rosling – Gapminder (2:17 to 6:06) videos about the third world myths. Don’t get overwhelmed with the Big Data buzz word, the destination to what your data speaks is important. In this blog post, we did not particularly look at any Big Data technologies. This is a set of questionnaire one needs to keep in mind as they embark their journey of Big Data. I did write some of the basics in my blog: Big Data – Big Hype yet Big Opportunity. Do let me know if these questions make sense?  Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL SERVER – 5 Tips for Improving Your Data with expressor Studio

    - by pinaldave
    It’s no secret that bad data leads to bad decisions and poor results.  However, how do you prevent dirty data from taking up residency in your data store?  Some might argue that it’s the responsibility of the person sending you the data.  While that may be true, in practice that will rarely hold up.  It doesn’t matter how many times you ask, you will get the data however they decide to provide it. So now you have bad data.  What constitutes bad data?  There are quite a few valid answers, for example: Invalid date values Inappropriate characters Wrong data Values that exceed a pre-set threshold While it is certainly possible to write your own scripts and custom SQL to identify and deal with these data anomalies, that effort often takes too long and becomes difficult to maintain.  Instead, leveraging an ETL tool like expressor Studio makes the data cleansing process much easier and faster.  Below are some tips for leveraging expressor to get your data into tip-top shape. Tip 1:     Build reusable data objects with embedded cleansing rules One of the new features in expressor Studio 3.2 is the ability to define constraints at the metadata level.  Using expressor’s concept of Semantic Types, you can define reusable data objects that have embedded logic such as constraints for dealing with dirty data.  Once defined, they can be saved as a shared atomic type and then re-applied to other data attributes in other schemas. As you can see in the figure above, I’ve defined a constraint on zip code.  I can then save the constraint rules I defined for zip code as a shared atomic type called zip_type for example.   The next time I get a different data source with a schema that also contains a zip code field, I can simply apply the shared atomic type (shown below) and the previously defined constraints will be automatically applied. Tip 2:     Unlock the power of regular expressions in Semantic Types Another powerful feature introduced in expressor Studio 3.2 is the option to use regular expressions as a constraint.   A regular expression is used to identify patterns within data.   The patterns could be something as simple as a date format or something much more complex such as a street address.  For example, I could define that a valid IP address should be made up of 4 numbers, each 0 to 255, and separated by a period.  So 192.168.23.123 might be a valid IP address whereas 888.777.0.123 would not be.   How can I account for this using regular expressions? A very simple regular expression that would look for any 4 sets of 3 digits separated by a period would be:  ^[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}$ Alternatively, the following would be the exact check for truly valid IP addresses as we had defined above:  ^(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])\.(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])$ .  In expressor, we would enter this regular expression as a constraint like this: Here we select the corrective action to be ‘Escalate’, meaning that the expressor Dataflow operator will decide what to do.  Some of the options include rejecting the offending record, skipping it, or aborting the dataflow. Tip 3:     Email pattern expressions that might come in handy In the example schema that I am using, there’s a field for email.  Email addresses are often entered incorrectly because people are trying to avoid spam.  While there are a lot of different ways to define what constitutes a valid email address, a quick search online yields a couple of really useful regular expressions for validating email addresses: This one is short and sweet:  \b[A-Z0-9._%+-]+@[A-Z0-9.-]+\.[A-Z]{2,4}\b (Source: http://www.regular-expressions.info/) This one is more specific about which characters are allowed:  ^([a-zA-Z0-9_\-\.]+)@((\[[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.)|(([a-zA-Z0-9\-]+\.)+))([a-zA-Z]{2,4}|[0-9]{1,3})(\]?)$ (Source: http://regexlib.com/REDetails.aspx?regexp_id=26 ) Tip 4:     Reject “dirty data” for analysis or further processing Yet another feature introduced in expressor Studio 3.2 is the ability to reject records based on constraint violations.  To capture reject records on input, simply specify Reject Record in the Error Handling setting for the Read File operator.  Then attach a Write File operator to the reject port of the Read File operator as such: Next, in the Write File operator, you can configure the expressor operator in a similar way to the Read File.  The key difference would be that the schema needs to be derived from the upstream operator as shown below: Once configured, expressor will output rejected records to the file you specified.  In addition to the rejected records, expressor also captures some diagnostic information that will be helpful towards identifying why the record was rejected.  This makes diagnosing errors much easier! Tip 5:    Use a Filter or Transform after the initial cleansing to finish the job Sometimes you may want to predicate the data cleansing on a more complex set of conditions.  For example, I may only be interested in processing data containing males over the age of 25 in certain zip codes.  Using an expressor Filter operator, you can define the conditional logic which isolates the records of importance away from the others. Alternatively, the expressor Transform operator can be used to alter the input value via a user defined algorithm or transformation.  It also supports the use of conditional logic and data can be rejected based on constraint violations. However, the best tip I can leave you with is to not constrain your solution design approach – expressor operators can be combined in many different ways to achieve the desired results.  For example, in the expressor Dataflow below, I can post-process the reject data from the Filter which did not meet my pre-defined criteria and, if successful, Funnel it back into the flow so that it gets written to the target table. I continue to be impressed that expressor offers all this functionality as part of their FREE expressor Studio desktop ETL tool, which you can download from here.  Their Studio ETL tool is absolutely free and they are very open about saying that if you want to deploy their software on a dedicated Windows Server, you need to purchase their server software, whose pricing is posted on their website. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – Shrinking Database is Bad – Increases Fragmentation – Reduces Performance

    - by pinaldave
    Earlier, I had written two articles related to Shrinking Database. I wrote about why Shrinking Database is not good. SQL SERVER – SHRINKDATABASE For Every Database in the SQL Server SQL SERVER – What the Business Says Is Not What the Business Wants I received many comments on Why Database Shrinking is bad. Today we will go over a very interesting example that I have created for the same. Here are the quick steps of the example. Create a test database Create two tables and populate with data Check the size of both the tables Size of database is very low Check the Fragmentation of one table Fragmentation will be very low Truncate another table Check the size of the table Check the fragmentation of the one table Fragmentation will be very low SHRINK Database Check the size of the table Check the fragmentation of the one table Fragmentation will be very HIGH REBUILD index on one table Check the size of the table Size of database is very HIGH Check the fragmentation of the one table Fragmentation will be very low Here is the script for the same. USE MASTER GO CREATE DATABASE ShrinkIsBed GO USE ShrinkIsBed GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Create FirstTable CREATE TABLE FirstTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_FirstTable_ID] ON FirstTable ( [ID] ASC ) ON [PRIMARY] GO -- Create SecondTable CREATE TABLE SecondTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_SecondTable_ID] ON SecondTable ( [ID] ASC ) ON [PRIMARY] GO -- Insert One Hundred Thousand Records INSERT INTO FirstTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Insert One Hundred Thousand Records INSERT INTO SecondTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO Let us check the table size and fragmentation. Now let us TRUNCATE the table and check the size and Fragmentation. USE MASTER GO CREATE DATABASE ShrinkIsBed GO USE ShrinkIsBed GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Create FirstTable CREATE TABLE FirstTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_FirstTable_ID] ON FirstTable ( [ID] ASC ) ON [PRIMARY] GO -- Create SecondTable CREATE TABLE SecondTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_SecondTable_ID] ON SecondTable ( [ID] ASC ) ON [PRIMARY] GO -- Insert One Hundred Thousand Records INSERT INTO FirstTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Insert One Hundred Thousand Records INSERT INTO SecondTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO You can clearly see that after TRUNCATE, the size of the database is not reduced and it is still the same as before TRUNCATE operation. After the Shrinking database operation, we were able to reduce the size of the database. If you notice the fragmentation, it is considerably high. The major problem with the Shrink operation is that it increases fragmentation of the database to very high value. Higher fragmentation reduces the performance of the database as reading from that particular table becomes very expensive. One of the ways to reduce the fragmentation is to rebuild index on the database. Let us rebuild the index and observe fragmentation and database size. -- Rebuild Index on FirstTable ALTER INDEX IX_SecondTable_ID ON SecondTable REBUILD GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO You can notice that after rebuilding, Fragmentation reduces to a very low value (almost same to original value); however the database size increases way higher than the original. Before rebuilding, the size of the database was 5 MB, and after rebuilding, it is around 20 MB. Regular rebuilding the index is rebuild in the same user database where the index is placed. This usually increases the size of the database. Look at irony of the Shrinking database. One person shrinks the database to gain space (thinking it will help performance), which leads to increase in fragmentation (reducing performance). To reduce the fragmentation, one rebuilds index, which leads to size of the database to increase way more than the original size of the database (before shrinking). Well, by Shrinking, one did not gain what he was looking for usually. Rebuild indexing is not the best suggestion as that will create database grow again. I have always remembered the excellent post from Paul Randal regarding Shrinking the database is bad. I suggest every one to read that for accuracy and interesting conversation. Let us run following script where we Shrink the database and REORGANIZE. -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO -- Shrink the Database DBCC SHRINKDATABASE (ShrinkIsBed); GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO -- Rebuild Index on FirstTable ALTER INDEX IX_SecondTable_ID ON SecondTable REORGANIZE GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO You can see that REORGANIZE does not increase the size of the database or remove the fragmentation. Again, I no way suggest that REORGANIZE is the solution over here. This is purely observation using demo. Read the blog post of Paul Randal. Following script will clean up the database -- Clean up USE MASTER GO ALTER DATABASE ShrinkIsBed SET SINGLE_USER WITH ROLLBACK IMMEDIATE GO DROP DATABASE ShrinkIsBed GO There are few valid cases of the Shrinking database as well, but that is not covered in this blog post. We will cover that area some other time in future. Additionally, one can rebuild index in the tempdb as well, and we will also talk about the same in future. Brent has written a good summary blog post as well. Are you Shrinking your database? Well, when are you going to stop Shrinking it? Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Index, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • SQL SERVER – Step by Step Guide to Beginning Data Quality Services in SQL Server 2012 – Introduction to DQS

    - by pinaldave
    Data Quality Services is a very important concept of SQL Server. I have recently started to explore the same and I am really learning some good concepts. Here are two very important blog posts which one should go over before continuing this blog post. Installing Data Quality Services (DQS) on SQL Server 2012 Connecting Error to Data Quality Services (DQS) on SQL Server 2012 This article is introduction to Data Quality Services for beginners. We will be using an Excel file Click on the image to enlarge the it. In the first article we learned to install DQS. In this article we will see how we can learn about building Knowledge Base and using it to help us identify the quality of the data as well help correct the bad quality of the data. Here are the two very important steps we will be learning in this tutorial. Building a New Knowledge Base  Creating a New Data Quality Project Let us start the building the Knowledge Base. Click on New Knowledge Base. In our project we will be using the Excel as a knowledge base. Here is the Excel which we will be using. There are two columns. One is Colors and another is Shade. They are independent columns and not related to each other. The point which I am trying to show is that in Column A there are unique data and in Column B there are duplicate records. Clicking on New Knowledge Base will bring up the following screen. Enter the name of the new knowledge base. Clicking NEXT will bring up following screen where it will allow to select the EXCE file and it will also let users select the source column. I have selected Colors and Shade both as a source column. Creating a domain is very important. Here you can create a unique domain or domain which is compositely build from Colors and Shade. As this is the first example, I will create unique domain – for Colors I will create domain Colors and for Shade I will create domain Shade. Here is the screen which will demonstrate how the screen will look after creating domains. Clicking NEXT it will bring you to following screen where you can do the data discovery. Clicking on the START will start the processing of the source data provided. Pre-processed data will show various information related to the source data. In our case it shows that Colors column have unique data whereas Shade have non-unique data and unique data rows are only two. In the next screen you can actually add more rows as well see the frequency of the data as the values are listed unique. Clicking next will publish the knowledge base which is just created. Now the knowledge base is created. We will try to take any random data and attempt to do DQS implementation over it. I am using another excel sheet here for simplicity purpose. In reality you can easily use SQL Server table for the same. Click on New Data Quality Project to see start DQS Project. In the next screen it will ask which knowledge base to use. We will be using our Colors knowledge base which we have recently created. In the Colors knowledge base we had two columns – 1) Colors and 2) Shade. In our case we will be using both of the mappings here. User can select one or multiple column mapping over here. Now the most important phase of the complete project. Click on Start and it will make the cleaning process and shows various results. In our case there were two columns to be processed and it completed the task with necessary information. It demonstrated that in Colors columns it has not corrected any value by itself but in Shade value there is a suggestion it has. We can train the DQS to correct values but let us keep that subject for future blog posts. Now click next and keep the domain Colors selected left side. It will demonstrate that there are two incorrect columns which it needs to be corrected. Here is the place where once corrected value will be auto-corrected in future. I manually corrected the value here and clicked on Approve radio buttons. As soon as I click on Approve buttons the rows will be disappeared from this tab and will move to Corrected Tab. If I had rejected tab it would have moved the rows to Invalid tab as well. In this screen you can see how the corrected 2 rows are demonstrated. You can click on Correct tab and see previously validated 6 rows which passed the DQS process. Now let us click on the Shade domain on the left side of the screen. This domain shows very interesting details as there DQS system guessed the correct answer as Dark with the confidence level of 77%. It is quite a high confidence level and manual observation also demonstrate that Dark is the correct answer. I clicked on Approve and the row moved to corrected tab. On the next screen DQS shows the summary of all the activities. It also demonstrates how the correction of the quality of the data was performed. The user can explore their data to a SQL Server Table, CSV file or Excel. The user also has an option to either explore data and all the associated cleansing info or data only. I will select Data only for demonstration purpose. Clicking explore will generate the files. Let us open the generated file. It will look as following and it looks pretty complete and corrected. Well, we have successfully completed DQS Process. The process is indeed very easy. I suggest you try this out yourself and you will find it very easy to learn. In future we will go over advanced concepts. Are you using this feature on your production server? If yes, would you please leave a comment with your environment and business need. It will be indeed interesting to see where it is implemented. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Business Intelligence, Data Warehousing, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Data Quality Services, DQS

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  • MySQL – Scalability on Amazon RDS: Scale out to multiple RDS instances

    - by Pinal Dave
    Today, I’d like to discuss getting better MySQL scalability on Amazon RDS. The question of the day: “What can you do when a MySQL database needs to scale write-intensive workloads beyond the capabilities of the largest available machine on Amazon RDS?” Let’s take a look. In a typical EC2/RDS set-up, users connect to app servers from their mobile devices and tablets, computers, browsers, etc.  Then app servers connect to an RDS instance (web/cloud services) and in some cases they might leverage some read-only replicas.   Figure 1. A typical RDS instance is a single-instance database, with read replicas.  This is not very good at handling high write-based throughput. As your application becomes more popular you can expect an increasing number of users, more transactions, and more accumulated data.  User interactions can become more challenging as the application adds more sophisticated capabilities. The result of all this positive activity: your MySQL database will inevitably begin to experience scalability pressures. What can you do? Broadly speaking, there are four options available to improve MySQL scalability on RDS. 1. Larger RDS Instances – If you’re not already using the maximum available RDS instance, you can always scale up – to larger hardware.  Bigger CPUs, more compute power, more memory et cetera. But the largest available RDS instance is still limited.  And they get expensive. “High-Memory Quadruple Extra Large DB Instance”: 68 GB of memory 26 ECUs (8 virtual cores with 3.25 ECUs each) 64-bit platform High I/O Capacity Provisioned IOPS Optimized: 1000Mbps 2. Provisioned IOPs – You can get provisioned IOPs and higher throughput on the I/O level. However, there is a hard limit with a maximum instance size and maximum number of provisioned IOPs you can buy from Amazon and you simply cannot scale beyond these hardware specifications. 3. Leverage Read Replicas – If your application permits, you can leverage read replicas to offload some reads from the master databases. But there are a limited number of replicas you can utilize and Amazon generally requires some modifications to your existing application. And read-replicas don’t help with write-intensive applications. 4. Multiple Database Instances – Amazon offers a fourth option: “You can implement partitioning,thereby spreading your data across multiple database Instances” (Link) However, Amazon does not offer any guidance or facilities to help you with this. “Multiple database instances” is not an RDS feature.  And Amazon doesn’t explain how to implement this idea. In fact, when asked, this is the response on an Amazon forum: Q: Is there any documents that describe the partition DB across multiple RDS? I need to use DB with more 1TB but exist a limitation during the create process, but I read in the any FAQ that you need to partition database, but I don’t find any documents that describe it. A: “DB partitioning/sharding is not an official feature of Amazon RDS or MySQL, but a technique to scale out database by using multiple database instances. The appropriate way to split data depends on the characteristics of the application or data set. Therefore, there is no concrete and specific guidance.” So now what? The answer is to scale out with ScaleBase. Amazon RDS with ScaleBase: What you get – MySQL Scalability! ScaleBase is specifically designed to scale out a single MySQL RDS instance into multiple MySQL instances. Critically, this is accomplished with no changes to your application code.  Your application continues to “see” one database.   ScaleBase does all the work of managing and enforcing an optimized data distribution policy to create multiple MySQL instances. With ScaleBase, data distribution, transactions, concurrency control, and two-phase commit are all 100% transparent and 100% ACID-compliant, so applications, services and tooling continue to interact with your distributed RDS as if it were a single MySQL instance. The result: now you can cost-effectively leverage multiple MySQL RDS instance to scale out write-intensive workloads to an unlimited number of users, transactions, and data. Amazon RDS with ScaleBase: What you keep – Everything! And how does this change your Amazon environment? 1. Keep your application, unchanged – There is no change your application development life-cycle at all.  You still use your existing development tools, frameworks and libraries.  Application quality assurance and testing cycles stay the same. And, critically, you stay with an ACID-compliant MySQL environment. 2. Keep your RDS value-added services – The value-added services that you rely on are all still available. Amazon will continue to handle database maintenance and updates for you. You can still leverage High Availability via Multi A-Z.  And, if it benefits youra application throughput, you can still use read replicas. 3. Keep your RDS administration – Finally the RDS monitoring and provisioning tools you rely on still work as they did before. With your one large MySQL instance, now split into multiple instances, you can actually use less expensive, smallersmaller available RDS hardware and continue to see better database performance. Conclusion Amazon RDS is a tremendous service, but it doesn’t offer solutions to scale beyond a single MySQL instance. Larger RDS instances get more expensive.  And when you max-out on the available hardware, you’re stuck.  Amazon recommends scaling out your single instance into multiple instances for transaction-intensive apps, but offers no services or guidance to help you. This is where ScaleBase comes in to save the day. It gives you a simple and effective way to create multiple MySQL RDS instances, while removing all the complexities typically caused by “DIY” sharding andwith no changes to your applications . With ScaleBase you continue to leverage the AWS/RDS ecosystem: commodity hardware and value added services like read replicas, multi A-Z, maintenance/updates and administration with monitoring tools and provisioning. SCALEBASE ON AMAZON If you’re curious to try ScaleBase on Amazon, it can be found here – Download NOW. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: MySQL, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL SERVER – Repair a SQL Server Database Using a Transaction Log Explorer

    - by Pinal Dave
    In this blog, I’ll show how to use ApexSQL Log, a SQL Server transaction log viewer. You can download it for free, install, and play along. But first, let’s describe some disaster recovery scenarios where it’s useful. About SQL Server disaster recovery Along with database development and administration, you must work on a good recovery plan. Disasters do happen and no one’s immune. What you can do is take all actions needed to be ready for a disaster and go through it with minimal data loss and downtime. Besides creating a recovery plan, it’s necessary to have a list of steps that will be executed when a disaster occurs and to test them before a disaster. This way, you’ll know that the plan is good and viable. Testing can also be used as training for all team members, so they can all understand and execute it when the time comes. It will show how much time is needed to have your servers fully functional again and how much data you can lose in a real-life situation. If these don’t meet recovery-time and recovery-point objectives, the plan needs to be improved. Keep in mind that all major changes in environment configuration, business strategy, and recovery objectives require a new recovery plan testing, as these changes most probably induce a recovery plan changing and tweaking. What is a good SQL Server disaster recovery plan? A good SQL Server disaster recovery strategy starts with planning SQL Server database backups. An efficient strategy is to create a full database backup periodically. Between two successive full database backups, you can create differential database backups. It is essential is to create transaction log backups regularly between full database backups. Keep in mind that transaction log backups can be created only on databases in the full recovery model. In other words, a simple, but efficient backup strategy would be a full database backup every night, a transaction log backup every hour, or every 15 minutes. The frequency depends on how much data you can afford to lose and how busy the database is. Another option, instead of creating a full database backup every night, is to create a full database backup once a week (e.g. on Friday at midnight) and differential database backup every night until next Friday when you will create a full database backup again. Once you create your SQL Server database backup strategy, schedule the backups. You can do that easily using SQL Server maintenance plans. Why are transaction logs important? Transaction log backups contain transactions executed on a SQL Server database. They provide enough information to undo and redo the transactions and roll back or forward the database to a point in time. In SQL Server disaster recovery situations, transaction logs enable to repair a SQL Server database and bring it to the state before the disaster. Be aware that even with regular backups, there will be some data missing. These are the transactions made between the last transaction log backup and the time of the disaster. In some situations, to repair your SQL Server database it’s not necessary to re-create the database from its last backup. The database might still be online and all you need to do is roll back several transactions, such as wrong update, insert, or delete. The restore to a point in time feature is available in SQL Server, but for large databases, it is very time-consuming, as SQL Server first restores a full database backup, and then restores transaction log backups, one after another, up to the recovery point. During that time, the database is unavailable. This is where a SQL Server transaction log viewer can help. For optimal recovery, besides having a database in the full recovery model, it’s important that you haven’t manually truncated the online transaction log. This ensures that all transactions made after the last transaction log backup are still in the online transaction log. All you have to do is read and replay them. How to read a SQL Server transaction log? SQL Server doesn’t provide an option to read transaction logs. There are several SQL Server commands and functions that read the content of a transaction log file (fn_dblog, fn_dump_dblog, and DBCC PAGE), but they are undocumented. They require T-SQL knowledge, return a large number of not easy to read and understand columns, sometimes in binary or hexadecimal format. Another challenge is reading UPDATE statements, as it’s necessary to match it to a value in the MDF file. When you finally read the transactions executed, you have to create a script for it. How to easily repair a SQL database? The easiest solution is to use a transaction log reader that will not only read the transactions in the transaction log files, but also automatically create scripts for the read transactions. In the following example, I will show how to use ApexSQL Log to repair a SQL database after a crash. If a database has crashed and both MDF and LDF files are lost, you have to rely on the full database backup and all subsequent transaction log backups. In another scenario, the MDF file is lost, but the LDF file is available. First, restore the last full database backup on SQL Server using SQL Server Management Studio. I’ll name it Restored_AW2014. Then, start ApexSQL Log It will automatically detect all local servers. If not, click the icon right to the Server drop-down list, or just type in the SQL Server instance name. Select the Windows or SQL Server authentication type and select the Restored_AW2014 database from the database drop-down list. When all options are set, click Next. ApexSQL Log will show the online transaction log file. Now, click Add and add all transaction log backups created after the full database backup I used to restore the database. In case you don’t have transaction log backups, but the LDF file hasn’t been lost during the SQL Server disaster, add it using Add.   To repair a SQL database to a point in time, ApexSQL Log needs to read and replay all the transactions in the transaction log backups (or the LDF file saved after the disaster). That’s why I selected the Whole transaction log option in the Filter setup. ApexSQL Log offers a range of various filters, which are useful when you need to read just specific transactions. You can filter transactions by the time of the transactions, operation type (e.g. to read only data inserts), table name, SQL Server login that made the transaction, etc. In this scenario, to repair a SQL database, I’ll check all filters and make sure that all transactions are included. In the Operations tab, select all schema operations (DDL). If you omit these, only the data changes will be read so if there were any schema changes, such as a new function created, or an existing table modified, they will be ignored and database will not be properly repaired. The data repair for modified tables will fail. In the Tables tab, I’ll make sure all tables are selected. I will uncheck the Show operations on dropped tables option, to reduce the number of transactions. Click Next. ApexSQL Log offers three options. Select Open results in grid, to get a user-friendly presentation of the transactions. As you can see, details are shown for every transaction, including the old and new values for updated columns, which are clearly highlighted. Now, select them all and then create a redo script by clicking the Create redo script icon in the menu.   For a large number of transactions and in a critical situation, when acting fast is a must, I recommend using the Export results to file option. It will save some time, as the transactions will be directly scripted into a redo file, without showing them in the grid first. Select Generate reconstruction (REDO) script , change the output path if you want, and click Finish. After the redo T-SQL script is created, ApexSQL Log shows the redo script summary: The third option will create a command line statement for a batch file that you can use to schedule execution, which is not really applicable when you repair a SQL database, but quite useful in daily auditing scenarios. To repair your SQL database, all you have to do is execute the generated redo script using an integrated developer environment tool such as SQL Server Management Studio or any other, against the restored database. You can find more information about how to read SQL Server transaction logs and repair a SQL database on ApexSQL Solution center. There are solutions for various situations when data needs to be recovered, restored, or transactions rolled back. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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