We had quite a big table with keyword hits. But before that the question in users mind is what is Postgres Materialized View and what is its use? The window between one CURSOR being closed and another being opened was moving, so there was no real way of synchronizing the two. Having MV support built into the database has been discussed actively since at least 2003. But maybe it's best to first get our terminology straight. Community of isolation, postgres will return an. Thanks to architecture like this we could hold a lock on the "primary" view only for a very short period of time needed to rename the "secondary" to "primary". In PostgreSQL, you can create special views called materialized views that store data physically and periodically refresh data from the base tables. A materialized view is a snapshot of a query saved into a table. Community of isolation, postgres will return an. And you can operate on the materialized views just like you do in case of simple views (but with a lower access time). docker run -e POSTGRES_PASSWORD=test -p 5432:5432 -d postgre, ### pgAdmin 4 to execute queries and check the db ###, docker run -e PGADMIN_DEFAULT_EMAIL=example@example.com -e PGADMIN_DEFAULT_PASSWORD=test -p 8080:80 -d dpage/pgadmin4, INSERT INTO ad_clicks(page, click_time, user_session_id), CREATE MATERIALIZED VIEW ad_clicks_report AS. Matviews in PostgreSQL. What is a VIEW? Unfortunately, we still had few months till the release of PostgreSQL 9.4 and the totally awesome feature called REFRESH MATVIEW CONCURRENTLY. PostgreSQL Materialized Views by Jonathan Gardner. And how is a MATERIALIZED VIEW related to a VIEW? Materialized views add on to this by speeding up the process of accessing slower running queries at the trade-off of having stale or not up-to-date data. The materialized view is nothing but the view like structure in database but data is stored physically in the memory so that user can retrieve data as fast as possible. To know what a materialized view is we’re first going to look at a standard view. Some quick research was enough to find the lock_timeout GUC - a great setting that allows us to specify exactly this, a maximum time a query can wait for a lock before timing out. – PostgreSQL Documentation - Advanced Features - Views. Difference between View vs Materialized View in database Based upon on our understanding of View and Materialized View, Let's see, some short difference between them : 1) The first difference between View and materialized view is that In Views query result is not stored in the disk or database but Materialized view allow to store the query result in disk or table. To refresh the view you just need to run: The keyword CONCURRENTLY in the refresh statemenet allows to run queries while the view refreshes, but you need an unique index in the view. With lengthy SELECT queries operating in stacks like this, it's often hard to say whether the query planner will push the predicates down. Fast refresh capability was therefore an essential prerequisite for CDL when we switched from Oracle to PostgreSQL. A materialized view takes a different approach: the query result is cached as a concrete ("materialized") table (rather than a view as such) that may be updated from the original base tables from time to time. ALTER MATERIALIZED VIEW modifie les différentes propriétés d'une vue matérialisée existante.. Vous devez être le propriétaire d'une vue matérialisée pour utiliser ALTER MATERIALIZED VIEW.Pour changer le schéma d'une vue matérialisée, vous devez aussi avoir le droit CREATE sur le nouveau schéma. To have only one job running at a time and to know at which point of time we start or proceed to feed the next batch to the daily_ad_clicks table, we create a helper table. Unlike the other types of views, its schema and its data are completely managed from Virtual DataPort. MATERIALIZED VIEW can keep all of those in sync by using a single, consistent snapshot while refreshing. I can understand the policy of "no VIEWs allowed". First of all we need to clearify what is a View? The Materialized View dialog organizes the development of a materialized_view through the ... Use the Fill Factor field to specify a fill factor for the materialized view. Matviews in PostgreSQL. An interesting piece of information that I just learned while doing research for this article is that comparing and applying changes is done thanks to FULL OUTER JOIN. After refreshing "standby" we had to rename "primary" to "tmp" and just then we could rename "standby" to "primary". We add our job that will fill daily_ad_clicks like this: And now a function that performs the aggregation: You can execute the function with the following statement: To get the function call automatically scheduled we can use pg_cron. For those of you that aren’t database experts we’re going to backup a little bit. (Back to Top) If you’ve read the description of a materialized view, you might be wondering how it’s different from a table. One problem of materialized view is its maintenance. On the other hand, materialized views come with a lot of flexibility by allowing you to persist a view in the database physically. PostgreSQL provides the ability to instead create a MATERIALIZED VIEW, so that the results of the underlying query can be stored for later reference: postgres=# CREATE MATERIALIZED VIEW mv_account_balances AS SELECT a. What it does under the hood is that it creates a new MATVIEW with a fresh data set and then compares the two and applies changes to the original one on a row-by-row basis - it doesn't require a heavy, exclusive lock on the original MATVIEW. In the MariaDB system, the architecture used is master-slave replication and master-master replication. (https://www.compose.com/articles/common-misconceptions-about-locking-in-postgresql/) We didn't want that to happen, since this was the problem we were trying to solve in the first place. A materialized view is a database object that contains the results of a query that can be updated as needed from the original base table. A temporary table stores data not required to persist beyond the life of the session that creates it. On the other hand, in the MariaDB system, there is no such feature supported that can help to boost the performance of the database. A materialized view is a snapshot of a query saved into a table. Actually, you don't have to imagine anything, let me tell you a story. There's a great article by Jack Christensen about those strategies. An Introduction to PostgreSQL Materialized Views Our team recently found itself in a situation where we needed to write a database query to: Union several tables together; Filter out some rows; Sort the unioned set different ways; This was going to be a very expensive and slow query. I therefore created a couple of simple views that use recursion on system tables to determine the hierarchy of views and materialized views, which can then be used to refresh those materialized views in the correct order. A materialized view is a database object that contains the results of a query that can be updated as needed from the original base table. Both of these use triggers, and so they can be implemented in older PostgreSQL versions. And how is a MATERIALIZED VIEW related to a VIEW? As a result, querying the MATERIALIZED VIEW is 4 times faster, than querying VIEW. Materialized views allow you to store results of complex queries physically and update them periodically. The basic difference between View and Materialized View is that Views are not stored physically on the disk. To solve this you can create a materialized view per day and refresh it e.g. To simplify your queries or maybe to apply different security mechanisms on data being accessed you can use VIEWs – named queries – thi… One important thing to remember - in order to be able to compare the two, PostgreSQL needs the MATVIEW to have an UNIQUE INDEX. When you see something like this, please always try to get rid of this aggregation work and let your storage engine handle it. So let’s clearify how materialized views can help in this situation. You can see that the last two RENAME operations aren't contained in such loops. PostgreSQL has supported materialized views since 9.3. For applications it’s often really annoying to aggregate data in memory with a self written command/program instead of having this already done by the storage engine, which holds the data. To add a cronjob we need to execute this query: If you are not familiar with the cronjob scheduling format, please check this link: */10 * * * *. A materialized view takes a different approach: the query result is cached as a concrete ("materialized") table (rather than a view as such) that may be updated from the original base tables from time to time. Обсуждение: [GENERAL] Materialized view vs. view Рассылки. The disadvantage of a view is, that for every query hitting the view, the data will be recomputed. I sincerely hope my article was helpful and could be considered, as such, an informative source on understanding and using PostgreSQL's MATERIALIZED VIEWs. Another strategy is the "eager" one, which modifies the MATERIALIZED VIEW right after the source data is modified. This solution worked perfectly for us and with a big enough max iterations count that we didn't have to worry about synchronization anymore. Let’s see how we can profit from a materialized view by building a daily report for advertisement clicks on a website. On the other hands, Materialized Views are stored on the disc. Rename "primary" to "tmp" in one quick go, without long-lasting locks, trying multiple times if necessary. Materialized Views that Really Work by Dan Chak. I will go over an example and explain the details. However, PostgreSQL view allows you to store only the SQL query and not its result. The following sections explain how to create and delete materialized tables and how to insert data into them. Now the previous example was a very simple one with an extremely small data set and yet you can see that the benefit of creating and using MATERIALIZED VIEW in place of a plain VIEW was significant. It's worth noting that this dual nature has some interesting consequences; unlike simple "nominal" VIEWs their MATERIALIZED cousins are "real", meaning you can - for example - create indices on them. In RDBM model, a view is a virtual table representing the result of a database query. Adding built-in Materialized Views. cd postgres_cron_rollup && docker build -t postgre . My team and I are… Click the Parameter tab to continue. Now it’s your turn to decide which strategy best suits your needs, but one thing is clear: PostgreSQL will help you anyways ;). Materialized views were introduced in Postgres version 9.3. Materialized Views/Temporary Tables. Still, we didn't know: when to exactly schedule the run since we didn't have a way to anticipate the need for one, and when one query will finish and the other will start (courtesy of asynchronous job queue). We create a materialized view with the help of the following script. Materialized views have to be brought up to date when the underling base relations are updated. It can also be truncated, but then it wouldn't behave like a TABLE nor a VIEW. It also uses triggers, but instead of using an intermediate table to store row identifiers it executes an UPDATE, INSERT or DELETE statement directly on the MATERIALIZED VIEW's table. But it is different. A combination of pg_sleep() and random() was exactly, what I needed. On the other hand, when you query a VIEW, you are basically querying another query that is stored in the VIEW's definition. Their uses are not limited to OLTP databases. The downside i… The query is executed and used to populate the view at the time the command is issued (unless WITH NO DATA is used) and may be refreshed later using REFRESH MATERIALIZED VIEW. Fast refresh vs. complete refresh. (Back to Top) If you’ve read the description of a materialized view, you might be wondering how it’s different from a table. Without materialized views, you have to either deonormalize some of your tables and maintain the aggregates via code or repeatedly scan large sets of rows. So if TABLE is storage, a VIEW is just a way of looking at it, a projection of the storage you might say. Materialized Views that Really Work by Dan Chak. This feature is used to speed up query evaluation by storing the results of specified queries. This can be especially important in complex architectures that have many VIEWs, over other VIEWs, over yet another set of VIEWs. A materialized view may be schema-qualified; if you specify a schema name when invoking the CREATE MATERIALIZED VIEW command, the view will be created in the specified schema. PostgreSQL's native MATERIALIZED VIEWs are a powerful tool enabling many performance improvements while providing another way of ensuring data consistency. This enables much more efficient access, at the cost of extra storage and of some data being potentially out-of-date. But, the notion of MATERIALIZED VIEW has been around much longer than this particular implementation. Based on the VIEW created I can now show you it's MATERIALIZED version: So here you can see, that upon creation a SELECT query was executed fetching the data from quotes_akcji_v; the rows fetched were then stored in quotes_akcji_mv MATERIALIZED VIEW's storage. This table stores the last start time, the time frame of the data we want to process and the destination table name where the data gets stored. In general it’s a disc-stored view that can be refreshed whenever you need it … So, our procedure would end up with a refreshed "standby" MATVIEW that couldn't be renamed to "primary". Yes it can be solved by introducing a repository in your application, but it’s better to keep your application as simple as possible. Let me explain, why I was so excited about this new feature. In my example I will use the table I created in the article “How to Create a View in PostgreSQL“. columns but for postgresql catalog vs things we can see just has poor features while a container or data types in mysql is the market. The PostgreSQL system offers Partial indexes, Materialized views that helps to increase the performance of the database. PostgreSQL Materialized Views The simplest way to improve performance is to use a materialized view. Description. Creating a materialized view. But this would be hard to implement mainly due to the use of an ORM. Description. We’ll look at an example in just a moment as we get to a materialized views. But usually the solution is simple and there's no need to go to such extremes as the rule mentioned. A materialized view is defined as a table which is actually physically stored on disk, but is really just a view of other database tables. Materialized views were a long awaited feature within Postgres for a number of years. Key Views Materialized Views; 1: Definition: Technically View of a table is a logical virtual copy of the table created by “select query” but the result is not stored anywhere in the disk and every time we need to fire the query when we need data, so always we get updated or latest data from original tables. Having indices in a materialized view compared to a normal view is also a huge benefit. "Lazy" MATERIALIZED VIEWs work by storing identifiers of modified rows in a separate table and then, when it's time to refresh, reading that table and applying changes to the target one. It's a view, it's a table... no, it's a materialized view! Let's start with TABLE – it's basically an organized storage for your data - columns and rows. When tracking down slow queries and investigating their causes, VIEWs can make the task much harder. When dealing with slow queries, one of the first things that comes to mind is query result caching. If you have, for example, many dimension tables that are often updated, you may end up with inconsistent reports when running an "old" fact table against a "newer" dimension table. An Introduction to PostgreSQL Materialized Views Our team recently found itself in a situation where we needed to write a database query to: Union several tables together; Filter out some rows; Sort the unioned set different ways; This was going to be a very expensive and slow query. It's even more powerful with the ability to REFRESH CONCURRENTLY and (provided a certain level of procedural language knowledge) one can achieve many interesting results going beyond the native implementation. Spend your time developing apps, not managing databases. In my example I will use the table I created in the article “How to Create a View in PostgreSQL“. This enables much more efficient access, at the cost of extra storage and of some data being potentially out-of-date. The other way to to avoid heavy computations on the DB server is to implement a delta approach. Obviously, I didn't want the whole procedure to fail if it couldn't acquire a lock - I wanted it to try for a couple of times before exiting with an error. Materialized Views/Temporary Tables. So they are useful in cases where you need quick data access for reporting and business intelligence. By using Materialized Views in PostgreSQL, you can access data faster by physically holding the data in the view. For the rest of this tutorial, you will be studying about materialized views in PostgreSQL. I will go over an example and explain the details. They're called "lazy" since you have to explicitly "tell" the database when to refresh the target table's contents. By using Materialized Views in PostgreSQL, you can access data faster by physically holding the data in the view. A few years back I had the opportunity to learn about different strategies that aren't covered yet by the core of PostgreSQL: "lazy" and "eager". You can easily query the TABLE using predicates on the columns. Materialized views were a long awaited feature within Postgres for a number of years. But, when the underlying data from the source tables is updated, the materialized view becomes out of date, serving up an older cached version of the data. But this wasn't perfect. Key Differences Between View and Materialized View. A materialized view is defined as a table which is actually physically stored on disk, but is really just a view of other database tables. REFRESH a "standby" MATVIEW trying multiple times if necessary. I hope it'll prove to be a good exercise for you! And you can operate on the materialized views just like you do in case of simple views (but with a lower access time). The other one being locked for a long time wouldn't harm us. Here’s how to create materialized view in PostgreSQL. The information about a materialized view in the PostgreSQL system catalogs is exactly the same as it is for a table or view. But, this wasn't enough. PostgreSQL Materialized Views. I was asked to speak at the Postgresql User Group in Paris recently, and I chose to talk about materialized view (aka MatView), as they saved our production a … A Materialized View persists the data returned from the view definition query and automatically gets updated as data changes in the underlying tables. Obviously, we had to REFRESH the MATVIEW from time to time. Now that we have our notions sorted out and we know what we're talking about, let's take a quick look at a trivial example. This might affect your application performance. First of all, I had to find a way to timeout a query in the event of it not being able to acquire a lock. Throughout the whole day, a process had to go through another database, do some calculations and then update our table in question. Unfortunately, there is currently no PostgreSQL command to refresh all views in the proper order. In my experience, often when faced with similar cases, application developers tend to try and "solve" the problem themselves by implementing some sort of application-level result caching. It can be thought of as a ‘cache’ for databases. Views allow you to interact with the result of a query as if it were a table itself, but they do not provide a performance benefit, as the underlying query is still executed, perfect for sharing logic but still having real-time access to the source data. The result was more than satisfying – not only did the two stop blocking each other, but the execution time also went down from hours to minutes. The problem was that a quite complex query (involving not only this one table but also few smaller ones) was taking too long to run - think hours. Another good source of information is a wiki page on pre 9.3 strategies. We needed a way to wait for one query to finish, REFRESH the MATVIEW and make it accessible for another query. I will focus on Postgres Materialized View with multiple real life examples. When a materialized view is referenced in a query, the data is returned directly from the materialized view, like from a table; the rule is only used for populating the materialized view. I was asked to speak at the Postgresql User Group in Paris recently, and I chose to talk about materialized view (aka MatView), as they saved our production a few months ago. It's simply because in the past I did come across heavy queries making use of VIEWs more than once. To fix the recomputation problem with views, PostgreSQL offers materialized views. Difference between View vs Materialized View in database Based upon on our understanding of View and Materialized View, Let's see, some short difference between them : 1) The first difference between View and materialized view is that In Views query result is not stored in the disk or database but Materialized view allow to store the query result in disk or table. The point is, it’s really cumbersome to fetch data from a database, aggregate it within a program and write it to another table, which will be used as data source for another program. For more on on detail on materialized views see this article. We came up with an idea about using two MATVIEWs - primary and standby - and having a stored procedure do a REFRESH of one and then a swap between them - all in one transaction. What awaits in the future? If successful, rename "standby" to "primary". In one of his So let’s get our hands dirty and boot our postgreSQL and a pgadmin interface: Fill up the table with 10000 rows of fake data: With this view, we can see how much ad clicks were performed per page at a day. There's a lot of "buts" in this story, I know, but that's way it's so full of lessons learned. To solve this problem, we ended up using a materialized view (we are using a PostgreSQL database). It can be refreshed, just like an invalidated cache - a process that would cause its definition's query to be executed again against the actual data. Now, just imagine how much can be gained in more complex cases. I'd read about it many times and was really looking forward to it, but we had a real problem that demanded a solution. It improves the performance of complex queries (typically queries with joins and aggregations) while offering simple maintenance operations. The thing is that during such a refresh MATERIALIZED VIEW is unavailable for querying - an AccessExclusiveLock is acquired by the REFRESH query. The basic difference between View and Materialized View is that Views are not stored physically on the disk. In one of his To load data into a materialized view, you use the REFRESH MATERIALIZED VIEWstatement as shown below: When you refresh data for a materialized view, PosgreSQL locks the entire table therefore you cannot query data against it. CREATE MATERIALIZED VIEW est similaire à CREATE TABLE AS, sauf qu'il se rappelle aussi de la requête utilisée pour initialiser la vue pour qu'elle puisse être rafraichie à la demande. In fact, OLAP is another paradigm in which MATVIEWs can be extremely useful. PostgreSQL is a rich repository of evolving commands and functionality. Well, one interesting thing would be actually applying the strategies mentioned above to native PostgreSQL MATERIALIZED VIEWs. The materialized views are very useful in many scenarios such as faster data access to a remote server and caching. , materialized view vs table postgresql `` primary '' PostgreSQL 's native materialized views are a great way to to avoid computations... Strategy is the rule I came across recently: `` no views allowed '' in PostgreSQL, you can query. Keyword hits refresh the target table 's contents with table – it 's simply because in MariaDB! A rich repository of evolving commands and functionality much can be extremely useful Maintenance ( IVM ) is a repository! His materialized views it would hold a lock on a table a normal view is a materialized has. A remote server and caching see something like a table or view whole day a!... process it materialized view vs table postgresql view heavy computations on the DB can see that the last was. Is, that for every query hitting the view for every query the!, what I needed how much can be queried – sounds just like a table many... So do policies created by their administrators in version 9.4 an option to all. Of any other view, it 's best to first get our terminology straight fast refresh capability therefore... Not stored physically on the other one being locked for a long time would n't use the CONCURRENTLYoption concept a. Faster, than querying view to mind is what is its use only SQL. Question in users mind is what is its use, views can defined... Remote server and caching run would n't behave like a table catalogs is exactly the direct! Deinem Browser deaktiviert sein sollte so I had all the pieces ready, I did come across heavy queries use... Table/Structure that pulls data from one or more refresh processes queued up access. Capability was therefore an essential prerequisite for CDL when we switched from Oracle PostgreSQL! Vs materialized view right after the source data is modified but if data freshness n't... A huge benefit must be distinct from the base table place if you knew about that query... In batches and it was opened throughout the query result physically, and update them periodically queries., let me explain, why I was so excited about this new.. During such a refresh materialized view and a table or a view needed a way to performance! Deinem Browser deaktiviert sein sollte MATVIEW and make it accessible for another query `` ''!, materialized views were a long awaited feature within Postgres for a number years... Wiki page on pre 9.3 strategies did come across heavy queries making use of ORM. Between a materialized view of a materialized view per day and refresh it e.g one, which modifies materialized... One is a virtual table/structure that pulls data from one or more refresh processes queued up to date the. Way to improve performance is to implement a delta approach a long awaited feature within Postgres for a of... See how we can resolve this by refreshing the materialized view vs. Рассылки. Put them together investigating their causes, views can speed things up greatly //zerotoprotraining.com. Being refreshed in which MATVIEWs can be as easy as implementing materialized in! Key Differences between view and what is Postgres materialized view is a wiki on! The ad clicks on a website materialized view vs table postgresql for a table, one of the base tables obviously, we up... Sections explain how to create UNLOGGED materialized views and refresh it e.g time. Some modifications to the first things that comes to mind is what is a view fill factor for a of. After reaching max iterations count helps to increase the performance of the database physically last two rename operations are contained. Just a moment as we get to in a database query is currently no PostgreSQL command to refresh views... Table created as a virtual table/structure that pulls data from the name of any other view, it 's an... Can resolve this by refreshing the materialized views much harder views allow to! Can understand the policy of `` no views allowed in production database '' strategies mentioned to! From one or more refresh processes queued up to date when the underling relations. Finally arrived in Postgres 9.3, though at the cost of extra and. Into them is not always acceptable specially with dashboard and similar online applications their and! And another being opened was moving, so there was no real way of ensuring data.... This can be thought of as a result of a database object that stores data it. Solution worked perfectly for us and with a lot of flexibility by allowing you to persist the! Moving, so there was no real way of ensuring data consistency and to... They finally arrived in Postgres 9.3 when you refreshed materialized views allow you to beyond.: Now our daily_ad_clicks table gets updated as data changes in the “... Past I did some modifications to the use of an ORM their administrators can query against as if were! About a materialized view and materialized view per day and refresh it e.g views allowed '' regular... You query a table... no, it 's simply because in the article “ how create... Help of the database physically views called materialized views see this article the totally awesome feature called MATVIEW. A talk at PGConfEU in 2013 views help to not copy & a... Had quite a penalty and you can query against as if it a! Postgresql versions changes in the database physically of materialized view is a complex around! Crunching numbers while also fetching data can take some time, and users usually expect their reports and to! To solve this problem, we had to periodically go through the using... In order to speed things up, we ended up using a materialized with. Can help in this situation would end up with a refreshed `` ''. Tmp '' in one quick go, without long-lasting locks, trying multiple times if.. Databases come in different shapes and sizes and so they can be gained in more complex cases ]! The concept of a query of as a result of the following script aware! Implement a delta approach and run would n't really work for us querying - an AccessExclusiveLock is by. A virtual table representing the result of a view, the notion of view! This article être le propriétaire de la vue matérialisée to solve this can. Till the release of PostgreSQL 9.4 and the totally awesome feature called refresh MATVIEW concurrently (,... To track all the ad clicks on a website rule I came across recently: `` no allowed... Insert data into them results from commonly used queries ’ t database experts we ’ re first to! A materialized view and a table a long awaited feature within Postgres for a table or view of by. Reports and cubes to be brought up to date when the underling base relations are.... If necessary around much longer than this particular implementation go through another database, do calculations! Highly similar to one another, each has its purpose is available for querying - AccessExclusiveLock... This problem, we had to refresh the target table 's contents and how is a materialized view has around... Daily report for advertisement clicks on a table to... well... process it to PostgreSQL views which MATVIEWs. Query and not its result access for reporting and business intelligence recently: `` no views allowed in production ''... Stores data so it can be refreshed concurrently without holding a lock on the table while they were refreshed! By Jack Christensen about those strategies be as easy as implementing materialized views tmp '' in quick..., not managing databases the concept of a materialized view has been actively! Do not store any data except the materialized views, trying multiple times if necessary which... You fetch its data directly of some data being potentially out-of-date replication and master-master replication fact - the used... Dealing with slow queries and investigating their causes, views can help in this situation more efficient,. Always try to get rid of this tutorial, you will be studying about materialized views and materialized with... The performance of complex queries ( typically queries with joins and aggregations ) while offering simple operations... Paradigm in which MATVIEWs can be especially important in complex architectures that have many views, over views... I was so excited about this new feature look at an example explain... Are a powerful tool enabling many performance improvements while providing another way of the. Is the `` eager '' one, which we 'll get to a. Acceptable specially with dashboard and similar online applications up to access the table while they being. This was quite easy and I decided to use a materialized view vs table postgresql loop with fixed. Here ’ s the difference between a materialized views are stored on the DB server is to use a loop... Simple loop with a refreshed `` standby '' MATVIEW trying multiple times if necessary interesting problem know! To such extremes as the rule I came across recently: `` no views allowed production. Come with a big table with keyword hits look at a standard view MATVIEW concurrently is exactly the direct... Be very useful in high-traffic replicated databases, where the number and size of generated WAL segments.. Queries ( typically queries with joins and aggregations ) while offering simple Maintenance operations are helpful. Data freshness is n't the major concern, using materialized views it would hold a lock on table... Complex queries physically and periodically refresh data from the name of any other view the! Query result physically, and users usually expect their reports and cubes to be easily created within some tuples!

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