• Create an ADODB connection object which is required step for connecting to database as below.

Authentication using Id, Password and details.

• • Provider: For SQL server database the provider is “sqloledb”
  • Server: Open the SQL Server in your machine and Right click on the required Database/ click on properties.

• Click on “View connection Properties”

• User Name and Server details are required from this dialogue box

• objConnection.open “provider=sqloledb; Server=SDWA-160-PC; User Id=SDWA-160; Password=; Database=sample; Trusted_Connection=Yes”
• Hence, Connection setup completed and ready for execution.

• Enter the required SQL query to be executed.
• Execution of the query with the statement below.

• The above mentioned sample script has been executed and the value from the database is retrieved.

• Magic code is used to describe the code which handles the critical task without showing the complexity to present a simple interface.
• Some special characters is called magic code, as single quote( ‘ ), double quote (“), amperson (&) etc. It’s useful for beginner programmer.

• Error handling is the process of catching errors elevated from program and then taking correct action. If you would handle errors then the most common error checking methods given in PHP.
  • die() function
  • Custom errors and error triggers
  • Error reporting

• To write the PHP program you should check all possible error condition before checking and take appropriate action when required.
• The following example without having /tmp/test.xt file and with this file.

• We can write own function to handling any error. PHP provides a framework to define error handling function.
• This function must be able to handle a minimum of two parameters (error level and error message) but can accept up to five parameters (optionally: file, line-number, and the error context)

• These error report levels are the different types of error the user-defined error handler can be used.
• The errors are .E_ERROR, E_WARNING, E_PARSE, E_NOTICE, E_CORE_ERROR, E_CORE_WARNING, E_USER_ERROR, E_USER_WARNING, E_USER_NOTICE, E_STRICT, E_RECOVERABLE_ERROR, E_ALL
• These all errors handle to using set_error_handler function.

• We add a counter in that page.
• When a page load that counter value will increase.
• For storing its previous value we can use session, database etc.

• Joomla is a free and open-source Content Management System (CMS) for distributing web content.
• It is built on a Model-View-Controller (MVC) web application framework that can be used individually, and the CMS that allows to build powerful online applications.
• Joomla is one of the most popular website software’s.
• Joomla is an independent platform, user friendly, extendable, multilingual, accessible, responsive, search engine optimized and so much more.

• CMS is an application (web-based), that provides capabilities for multiple users with different permission levels to manage (all or a section of) content, data or information of a website project, or intranet application.
• Managing content refers to creating, editing, archiving, publishing, collaborating on, reporting, distributing website content, data and information.

• Joomla is used to whole world and millions of websites of all shapes and sizes. Joomla can be used for,
  • Corporate websites or portals, intranets and extranets.
  • Small business websites.
  • Online magazines, newspapers, and publications.
  • E-commerce and online reservations.
  • Government, non-profit and organizational websites.
  • Community-based, school and church websites or portals.
  • Personal or family homepages.

• Darwin Information Typing Architecture (DITA) is the most ideal approach to be brilliant about composition and distributing your business content.
• DITA is an open standard that portrays the engineering for making and overseeing data that isolates the substance from the arranging, takes into account a progressively streamlined substance creation process, and opens up the potential outcomes of acquainting less difficult methods for distributing with new advancements, as for cell phones. IBM, which created DITA initially, characterizes DITA as pursues:
• The Darwin Information Typing Architecture (DITA) is a XML-based, end-to-end design for composing, creating, and conveying specialized data.
• This engineering comprises of a lot of structure standards for making “data composed” modules at a subject dimension and for utilizing that content in conveyance modes, for example, online help and item bolster entryways on the Web.

• The information put away in your documentation has esteem.
• What’s more, whatever has an incentive to the association can be treated as an advantage. Making and afterward leaving that data inside a Word or PowerPoint record seriously constrains what you can do with it, and whatever you can do, you need to utilize manual, kludge approaches to do it.
• Making records with conventional instruments in static documents is a wasteful method for composing, refreshing, sharing, and dealing with your data.
• DITA is a general methodology that illuminates that wastefulness.
• DITA emphatically influences your substance in three principle ways;
• It streamlines your substance creation process expands the nature of your substance by institutionalizing it enables you to use your substance in a wide range of ways (reusing it, distributing to numerous configurations, deciphering it effectively)
• Despite the fact that there are numerous advantages to DITA, everything comes down to a certain something: being proficient with your substance so you can spare time and cash.

• DITA is certainly not a specific device. A wide range of apparatuses enable you to creator in DITA. Truth be told, choosing your instrument set is a piece of the procedure of DITA selection.
• DITA isn’t a layout, in spite of the fact that writers regularly use formats to make it considerably quicker and less demanding to compose.
• DITA isn’t a style direct, despite the fact that creators surely advantage from one, with or without DITA content.

• Try not to give the XML a chance to part of DITA alarm you.
• It’s simply the engineering underneath your substance. Each bit of substance gets put away inside labels-titles, sections, requested records-whatever you have to arrange your substance into a characterized set of theme types.
• DITA has a lot of guidelines that state what labels are permitted where, which gives you institutionalization of your substance.
• DITA XML at last completes three things.
• DITA XML composes your substance into points.
• Not all XML does this, but rather DITA has a center arrangement of theme types so you can put the correct kind of data in the correct subject sort, bringing about exceptionally usable substance.
• Consider subjects and even the XML inside themes like Lego® squares. You use them in different approaches to fabricate what you require. At last, they meet up to make more than the individual parts.
• XML isolates content from configuration, making it compact and adaptable. Your words and your arrangement are never again consolidated, which implies they can be overseen and refreshed autonomously.
• For instance, if your marking changes and you have to refresh the text dimension, shading, and style in the entirety of your archives, this will be a focal, once change for any substance put away without organization (in XML).
• XML enables the substance to be changed into numerous different arrangements. A great many people creator in XML and after that distribute to PDF, HTML, and either portable or ePub.
• It’s additionally conceivable to distribute to places you wouldn’t anticipate, similar to Open Office, Excel, and PowerPoint. You’re constrained just by your creative energy.

• The impala server consist of distributed and massively parallel processing info engine.
• It run on particular hosts among your CDH cluster with a various daemon processes.

• The core impala element may be a daemon method that runs on every node of the cluster, and its physically described by the impalad method.
• Then read and write a informative files; which accepts questions transmitted from the impala-shell command, Hue, JDBC, or ODBC; parallelizes the questions can seperate work to alternative nodes within the impala cluster; and transmits intermediate question results back to the central organizer node.
• The impala daemon running on any node, and that node is the organizer node for that question when You can submit a question.
• The other nodes transmit partial results back to the organizer, that constructs the ultimate result set for a question.
• You may continuously connect with a similar impala daemon for convenience.When running experiments with possibility through the impala-shell command.
• For clusters running production workloads, you would possibly load-balance between the nodes by submitting every question to a distinct impala daemon in round-robin vogue, exploitation the JDBC or ODBC interfaces.
• Its verify that nodes and may settle for new work. Through the impala daemons are in constant communication with the statestore.

• The impala element called the statestore checks on the health of impala daemons on all the nodes during a cluster, and unendingly relays its findings to every of these daemons.
• It is physically described by a daemon method named statestored; you simply would like such a method on one node within the cluster.
• If an impala node goes offline because of hardware failure, network error, software package issue, or alternative reason, the statestore informs all the opposite nodes so future queries will avoid creating requests to the unreached node.

• Performance and quantifiability enhancements.
• Integration with Apache koodoo.
• Security.
• The REFRESH statement currently updates data regarding HDFS block locations.
• [IMPALA-1654] many varieties of DDL operations will currently work on a spread of partitions.

• Impala can query many file format such as Parquet, Avro, Text, RCFile, SequenceFile
• Impala supports data stored in HDFS, Apache HBase and Amazon S3
• Impala supports multiple compression codecs:
  • Snappy (Recommended for its effective balance between compression ratio and decompression speed),
  • Gzip (Recommended when achieving the highest level of compression),
  • Deflate (not supported for text files), Bzip2, LZO (for text files only);
• Impala provides security through authorization based on Sentry (OS user ID)
  • Defining which users are allowed to access which resources,
  • What operations are they allowed to perform authentication based on Kerberos + ability to specify Active Directory username/password,
  • How does Impala verify the identity of the users to confirm that they are allowed exercise their privileges assigned to that user auditing,
  • What operations were attempted,
  • Did they succeed or not, allowing to track down suspicious activity; audit data are collected by Cloudera Manager;
• Impala supports SSL network encryption between Impala and client programs, and between the Impala-related daemons running on different nodes in the cluster;
• Impala allows to use UDFs and UDAFs;
• Impala orders the joins automatically to be the most efficient;
• Impala allows admission control – prioritization and queueing of queries within impala;
• Impala allows multi-user concurrent queries;
• Impala caches frequently accessed data in memory;
• Impala computes statistics (with COMPUTE STATS);
• Impala provides window functions (aggregation OVER PARTITION, RANK, LEAD, LAG, NTILE, and so on) – to provide more advanced SQL analytic capabilities (since version 2.0);
• Impala allows external joins and aggregation using disk (since version 2.0) – enables operations to spill to disk if their internal state exceeds the aggregate memory size;
• Impala allows subqueries inside WHERE clauses;
• Impala allows incremental statistics – only run statistics on the new or changed data for even faster statistics computations;
• Impala enables queries on complex nested structures including maps, structs and arrays;
• Impala enables merging (MERGE) in updates into existing tables;
• Impala enables some OLAP functions (ROLLUP, CUBE, GROUPING SET);
• Impala allows use of impala for inserts and updates into HBase.

• Lazy write is an effect caused by the use of a write-back cache. In a write-back cache, data is first written to the cache and then is later (during a particular time such as an idle machine cycle) is written to the disk or memory.
• This type of cache is more complex to implement, due to the need to track each locations that have been written over and what needs to be marked as dirty to fix later.

Lazy writer in Memory

• Lazy writer is a thread which is present for each NUMA node (and every instance has at least one) that scans through the buffer cache associated with that node.
• The lazy writer thread sleeps for a specific interval of time, and when it wakes up, it examines the size of the free buffer list.
• If the list is below a certain threshold, which depends on the total size of the buffer pool, the lazy writer thread scans the buffer pool to repopulate the free list.
• As buffers are added to the free list, they are also written to disk if they are dirty.
• So if there is no memory pressure and memory notification is stable it sleeps
• The sole purpose of Lazy Writer is to maintain some free buffers in the SQL Server Buffer Pool.
• Lazy writer runs periodically and check which buffers can be flushed and returned to the free pool.
• So even SQL Server is not under memory pressure, it will also work regularly.

• The inner query is executed only once.
• The inner query will get executed first and the output of the inner query used by the outer query.
• The inner query is not dependent on outer query.

• The outer query will get executed first and for every row of outer query, inner query will get executed.
• So the inner query will get executed as many times as number of rows in result of the outer query.
• The outer query output can use the inner query output for comparison. This means inner query and outer query dependent on each other.

• • The union operator combines the results of two or more queries into a single result set. But no.of columns must match in both/all the queries (and also the order) which are used for union.
  • We can union two tables irrespective of common field.
  • The UNION set operator is used for combining data from two tables which have columns with the same datatype.
    • Union – Returns with no duplicate rows.
    • Union all – Retruns with duplicate rows (No. of rows returned = No. of rows in Query1 + No. of rows in Query 2).

• We cannot use the union operator within a create view statement.
• We cannot use the union operator on text and image columns.

• Joins are used to extract information from more than one table based on the related column/coloums (PK and RFK) any no. of rows can be retrived based on matching colums.
• We can join two tables by ‘join’ if they have common field.
• A Join is used for displaying columns with the same or different names from different tables.
• Different types of joins are Inner join=equi join=join , outer join (Right outer join/right join, Left outer join / left join), Cross join , and full outer join/outer join.
• We can use join operator within a create view statement.
• We can use the join operator on text and image columns.

• SQLcode -501 pops up to show that , the Cursor identified in fetch or close statement is not opened.

• SQL error code means it return codes that are preceded by a minus sign (-) indicate that the SQL statement execution was unsuccessful.
  • If SQLCODE = 0, execution was successful.
  • If SQLCODE > 0, execution was successful with a warning.
  • If SQLCODE < 0, execution was not successful.
  • SQLCODE = 100, “no data” was found.