how materialized view works cassandra

And, generally, write you queries standalone. If I use 3 different tables for each model, how do I keep them consistent? That is Materialized View (MV) Materialized views suit for high cardinality data. You can also provide a link from the web. To remove the burden of keeping multiple tables in sync from a developer, Cassandra supports an experimental feature called materialized views. (A batch statement, would fail all 3 if one of them failed). I have a database server that has these features: 1. Assignee: Zhao Yang Reporter: Duarte Nunes Authors: Zhao Yang. Resolved; relates to. CASSANDRA-13127 Materialized Views: View row expires too soon. The FROM clause of the query can name tables, views, and other materialized views. These materialized view have data stored and when you query the materialized view,it returns data from the data stored. The developers of Scylla are working hard so that Scylla will not only have unparalleled performance (see our benchmarks) and reliability, but also have the features that our users want or expect for compatibility with the latest version of Apache Cassandra.. i am using Scylla Database and python Cassandra driver for my project, i used prepared statement on every query and it works, but when i use prepared statement on materialized view, it returns me nothing, can you please help me, is there any restriction or something else? Or the materialized view only uses disk for its primary keys f4, f1, f2, f3. Sometimes batch is useful. What is materialized views in oracle. Materialized views look exactly like tables to your LoopBack app. Fortunately 3.x versions of Cassandra can help you with duplicating data mutations by allowing you to construct views on existing tables.SQL developers learning Cassandra will find the concept of primary keys very familiar. The latest of these new features is Materialized Views, which will be an experimental feature in the upcoming Scylla release 2.0. 2. I kind of think it's the first case. New values are appended to a commitlog and ultimately flushed to a new data file on disk, but old values are purged in bulk during compaction. users_by_session_key, posts_by_id How much disk space the materialized view takes? (max 2 MiB). You will find key concepts explained, along with a working example that covers the basic steps to connect to and start working with this NoSQL database from Java. posts_by_category We will use the model to read data from the materialized view. Your supposition is correct -- it will take about the same amount of disk space as the base table. For example, a combination materialized view log can track both the primary key and the rowid of the affected row are recorded. It isn’t, however, the easiest one to use. The latest of these new features is Materialized Views, which will be an experimental feature in the upcoming Scylla release 2.0. Straight away I could see advantages of this. In most cases it does not fit to the project due to difficult modelling methodology and limitations around possible queries. When an MV is added to a table, Cassandra is forced to read the existing value as part of the UPDATE. If I remove the ttl and try again, it works as expected: truncate sbutnariu.test_bug; alter table sbutnariu.test_bug with default_time_to_live = 0; ... CASSANDRA-14441 Materialized view is not deleting/updating data when made changes in base table. CASSANDRA-13547 Filtered materialized views missing data. If you need to read a table with thousands of columns, you may have problems. So any CRUD operations performed on the base table are automatically persisted to the MV. E.g. Cassandra 3 (released Nov 2015) has support for materialised views. - as materialized view is implemented as a normal Cassandra table. We’ll be discussing performance of materialized views at Scylla Summit. cassandra datastax bigdata nosql If I have a base table with 10 fields, primary keys are f1, f2, f3. This is called fast refreshing. Although I can do some educated guess, but it would be great if someone familiar with materialized views can tell us the exact answer. By using our site, you acknowledge that you have read and understand our Cookie Policy, Privacy Policy, and our Terms of Service. High available by design. By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy, 2020 Stack Exchange, Inc. user contributions under cc by-sa, https://stackoverflow.com/questions/37505635/when-to-use-materialized-views/37519925#37519925, https://stackoverflow.com/questions/37505635/when-to-use-materialized-views/37506748#37506748. spent my time talking about the technology and especially providing advices and best practices for data modeling A local lock is acquired on the base table partition when generating the view update to ensure that the view updates are serialized. So if a query includes a partition key and indexed column, Cassandra can pin point the node to query and then use index on that node to get the result. Some performance tips: In this tutorial we will jump into working with Apache Cassandra with the goal of understanding the basics of Cassandras approach to querying. Each such view is a set of rows which corresponds to rows which are present in the underlying, or base, table specified in the SELECT statement. I create one materialized view from it, which include all the 10 fields, primary keys are f4, f1, f2, f3. Resolved; Show 1 more links (1 … While updating columns which is present in Materialized view gives below TRACE: I hope this answers your question. Can be globally distributed. This means that any user or application that needs to get this data can just query the materialized view itself, as though all of the data is in the one table, rather than running the expensive query that uses joins, functions, or subqueries. Secondary indexes are local to the node where indexed data is stored. Generate view updates for each materialized view of the base table. But you won't execute them because you're waiting for a successful response. Materialized views (MVs) could be used to implement multiple queries for a single table. The CREATE MATERIALIZED VIEW statement creates a new materialized view. It is different from simple oracle view.These materialized view have data stored and when you query the materialized view,it returns data from the data stored. This denormalization allows for very fast lookups of data in each view using the normal Cassandra read path. let’s consider a table Team_data in which id, name, address are the fields. Your Questions Answered below : CQL commands. And in case with materialized views, if anything new is written to the base table, the materialized view itself will have to be changed. A materialized view can combine all of that into a single result set that’s stored like a table. Resolved; Resolved; CASSANDRA-11500 Obsolete MV entry may not be properly deleted. Cassandra does not send mutation to materialized view in above condition. Materialized views work particularly well with immutable insert-only data, but should not be used in case of low-cardinality data. The efficiency of the maintenance of these views is a key factor of the usability of the system. Cassandra is optimized for writes and you will only get happy when you're using the cassandra features. It seems to me that if you want to keep the Posts or Users consistent across queries, then I have to use materialized views. The Materialized View is like a snapshot or picture of the original base tables. The perfect solution is a interface for your database. Resolved; Show 1 more links (1 relates to) Activity. People. There are two ways we can do this in Cassandra efficiently 1) secondary indexes and 2) materialized view. I noticed that I get the error batch with conditions cannot span multiple tables, which means I have to insert it one at a time into each separate table, which can cause consistency problems if one of the queries fails. Cassandra is a scalable NoSQL database that provides continuous availability with no single point of failure and gives the ability to handle large amounts of data with exceptional performance. CASSANDRA-11500 Obsolete MV entry may not be properly deleted. I guess my other question is when would it ever be okay for data to be inconsistent? No, you shouldn't always use materialized views. The new CQL statements for Materialized Views are very similar to the statements to those for Tables. Votes: 0 Vote for this issue Watchers: 13 Start watching this issue; Dates. I kind of think it's the first case. users_by_email Fortunately 3.x versions of Cassandra can help you with duplicating data mutations by allowing you to construct views on existing tables.SQL developers learning Cassandra will find the concept of primary keys very familiar. Cassandra will keep data in-sync between tables and materialized views based on those tables. let’s understand with an example. let’s discuss one by one. Materialized views allow fast lookup of data using the normal read path. Prerequisite – Concept of Indexing, Concept of Materialized Views In this article, we will see how we can do local indexing and how it works and how materialized views works internally. But there's are also some use case for the materialized views: If you haven't the time for this application but you need this feature, use materialized views. Primarily, since materialized views live in Cassandra they can offer at most what Cassandra offers, namely a highly available, eventually consistent version of materialized views. If you need to read a table with thousands of columns, you may have problems. You can also provide a link from the web. But unlike View, the Materialized View are precomputed and stored on a disk like an object, and they are not updated each time they are used. Such data is exposed by Cosmos DB Change Feed and consumed by an Azure Function (via Change … We also discuss How we can create, Alter and Drop Materialized views. Allows applications to write to any node anywhere, anytime. by Tetsuo Seto. Reviewers: Alex Petrov. So, since it makes sense to have consistency, then it seems to me that I will always want to use materialized views, and have to take the read before write penalty. 4. 6. By using materialized views Cassandra can abstract some of this away from the developer as it maintains the additional tables created during the materialized view … ALTER KEYSPACE. * * Shows using Materialized View pattern, get, get_range_slices, key slices. MVs are basically a view of another table. However, LoopBack doesn’t provides define and automigrate for Materialized Views. I'm not sure when I should make separate tables or materialized views. Thus, we need to use db.createModel LoopBack operation and create a model for each materialized view. Let’s have a look. 5. Resolved; CASSANDRA-13409 Materialized Views: View cells are resurrected. First, we need to create a table. posts_by_user. Another good explanation of materialized views can be found in this blog entry. A combination materialized view log works in the same manner as a materialized view log that tracks only one type of value, except that more than one type of value is recorded. (Btw i dont mean consistency across replicas when i say consistency, but consistency in data for the 3 Posts tables). Fortunately there is a way to refresh only the changed rows in a materialized view's base table. SQL CQL Elaboration; Database: Keyspace: These two concepts are relatively similar as both contain tables. A materialized view is a table built from data from another table, the base table, with new primary key and new properties. Basically you can now have one ‘user’ table and a ‘user_email’ view that contains the same data with a different partition key we can then query. Let’s first define the base table such that student_marks is the base table for getting the highest marks in class. People. After the database is pre-populated, * this class mocks a user interaction to perform a hotel search based on * city, selects one, then looks at some surrounding points of interest for * that hotel. Or the materialized view only uses disk for its primary keys f4, f1, f2, f3. Create a materialized view in Cassandra 3.0 and later. In DataStax Distribution of Apache Cassandra ™ and later, a materialized view is a table built from data in another table with a new primary key and new properties. This view will always reflect the state of the underlying table. Resolved ; Activity. In this application, you handle all your different tables. Cassandra 3 (released Nov 2015) has support for materialised views. Cassandra does not provide a way to automatically detect and fix such inconsistencies other than dropping and recreating the materialized view, which is not an ideal solution in production: DROP MATERIALIZED VIEW users_by_name; CREATE MATERIALIZED VIEW IF NOT EXISTS users_by_name AS SELECT * FROM users WHERE name IS NOT NULL AND email IS NOT NULL … cassandra datastax bigdata nosql. If your application needs a full consistency, not only eventually use another solution. Cassandra; CASSANDRA-13565; Materialized view usage of commit logs requires large mutation but commitlog_segment_size_in_mb=2048 causes exception Did a quick demo on local system with your table structure and below is TRACE output. On the other hands, Materialized Views are stored on the disc. Works on a set of rows matching the SELECT statement to return a single value. The materialized view is implemented as a distinct table, and no data de-duplication is done. Commands specific to the Cassandra Query Language shell (cqlsh) utility. A materialized view can combine all of that into a single result set that’s stored like a table. Straight away I could see advantages of this. Cassandra will keep data in-sync between tables and materialized views based on those tables. In your first paragraph you mention you mention the tradeoff is time vs performance. Read my deep dive blog post for all the trade-offs when using materialized views. Recall that Cassandra avoids reading existing values on UPDATE. There are two ways we can do this in Cassandra efficiently 1) secondary indexes and 2) materialized view. This means that any user or application that needs to get this data can just query the materialized view itself, as though all of the data is in the one table, rather than running the expensive query that uses joins, functions, or subqueries. No, you shouldn't always use materialized views. Materialized views handle automated server-side denormalization, removing the need for client side handling of this denormalization and ensuring eventual consistency between the base and view data. I have time so id like to make these 3 different tables instead of materialized views. Cassandra has limitations when it comes to the partition size and number of values: 100 MB and 2 billion respectively. So any CRUD operations performed on the base table are automatically persisted to the MV. Changes to the base table data automatically add and update data in a MV. If you also need real updates instead of upserts on all tables: use materialized views. The basic difference between View and Materialized View is that Views are not stored physically on the disk. For example, a combination materialized view log can track both the primary key and the rowid of the affected row are recorded. Materialized views handle automated server-side denormalization, removing the need for client side handling of this denormalization and ensuring eventual consistency between the base and view data. However materialized views I read have a read before write latency. drop materialized view log on t ; create materialized view log on t with sequence, ( VAL ), primary key ; create materialized view log on t with sequence, ( VAL ), primary key * ERROR at line 1: ORA-00922: missing or invalid option Omitting the comma before the column list works better. ... it works as expected: ... CASSANDRA-14441 Materialized view is not deleting/updating data when made changes in base table. ALTER … (max 2 MiB). Created: 16/Jan/17 20:18 Updated: 16/Apr/19 09:30 … ; View can be defined as a virtual table created as a result of the query expression. So hoping someone can provide more clarity for me for how to handle multiple queries in cassandra on a 'theoretical model` like Users or Posts. create materialized view log on t with sequence ( VAL ), primary key; Materialized view log created. Automatic workload and data balancing. Community ♦ 1 1 1 silver badge. Resolved; relates to. Materialized Views were introduced a few years ago with the intention to help with that, although later they appeared not to be so perfect. The sample simulates one or more IoT Devices whose generated data needs to be sent, received and processed in near-real time. I think what you are looking is present in detail in the below link ; -, http://www.datastax.com/dev/blog/materialized-view-performance-in-cassandra-3-x, Click here to upload your image Azure Function; Cosmos DB; Cosmos DB Change Feed; The high-level architecture is the following one: Device simulator writes JSON data to Cosmos DB into raw collection. A materialized view cannot be directly updated, but updates to the base table will cause corresponding updates in the view. I am wondering what's the cost for the disk space for the materialized views? They support pretty much … A materialized view is a table that is managed by Cassandra. As the arrows in the figure show, the app can only read from the materialized view. Resolved; CASSANDRA-11500 Obsolete MV entry may not be properly deleted. Don't execute queries with ALLOW FILTERING. I'm learning Cassandra now and I understand I should make a table for each query. You have a performance trade off but in this scenario, the time is more important. Assignee: Zhao Yang … A materialized view is a read-only table that automatically duplicates, persists and maintains a subset of data from a base table . Queries are optimized by the primary key definition. By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy, 2020 Stack Exchange, Inc. user contributions under cc by-sa, https://stackoverflow.com/questions/42085258/how-cassandra-store-data-for-materialized-views/42095435#42095435, https://stackoverflow.com/questions/42085258/how-cassandra-store-data-for-materialized-views/42088225#42088225. That is Materialized View (MV) Materialized views suit for high cardinality data. Generally, remember one important thing: Cassandra has an eventually consistency model. CQL commands. A primary key of a Materialized View must contain all columns from the primary key of the base table Any materialized view must map one CQL row from the base table to precisely one other row in the materialized view. How Cassandra store data for materialized views. Thus, we need to use db.createModel LoopBack operation and create a model for each materialized view. In the current versions of Cassandra there are a number of limitations on the definition of Materialized Views. Doesn't seem right. A query language that looks a lot like SQL.With the list of features above, why don’t we all use Cassandra for all our database needs? In this application, you handle all your different tables. You alter/add the order of primary keys on the MV. SQL with sharding. Materialized Views with Cassandra May 31st, 2016. That means: If you use qourum, you will have consistency but not every time. In Cassandra Materialized views play an important role such that Materialized views are suited for high cardinality data. Real-Time Materialized Views with Cosmos DB. Step 3 : Create models for materialized views. See more info in … Don't use token ranges or IN operator on partition keys :), Click here to upload your image Learn about materialized views, which are tables with data that is automatically inserted and updated from another base table. In this context, "processed" means: Provide, for each device, the sum of the sent value data and also the last sent value. I din'd find articles that specify the cost of disk space for materialized views. It is different from simple oracle view. Changes keyspace replication strategy and enables or disables commit log. I kind of think it's the first case. Materialized view performance in Cassandra 3.x; Performance considerations . This view will always reflect the state of the underlying table. Before a materialized view can perform a fast refresh however it needs a mechanism to capture any changes made to its base table. Thanks. The perfect solution is a interface for your database. Cassandra has limitations when it comes to the partition size and number of values: 100 MB and 2 billion respectively. If you need a better consistency: Use QUORUM, never use ALL. This database uses a ring design instead of using a master-slave architecture. Now i have 'posts_by_id' but no 'posts_By_category' table. If a success comes back, you execute a batch query. So how would i handle data consistency of 3 tables? We will use the model to read data from the materialized view. In Cassandra, the Materialized view handles the server-side de-normalization and in between the base table and materialized view table ensure the eventual consistency. Changes the table properties of a materialized view. Basically you can now have one ‘user’ table and a ‘user_email’ view that contains the same data with a different partition key we can then query. Materialized views are a feature, first released in Cassandra 3.0, which provide automatic maintenance of a shadow table (the materialized view) to a base table with a different partition key thus allowing efficient select for data with different keys.. Apache Cassandra is one of the most popular NoSQL databases. Between your heartbeats or between execution another query with QUORUM, you got 10 other events with the same partition key. In this screencast, Principal Engineer and Cassandra committer Gary Dusbabek provides an overview of Materialized Views, a feature added in Cassandra 3.0.Materialized Views allow you to automatically replicate primary data into other tables. Materialized views are designed to alleviate the pain for developers, but are essentially a trade-off of performance for connectedness. But please keep in mind: Use only a batch for the same partition keys. However, materialized views do not have the same write performance as normal table writes because the database performs an additional read-before-write operation to update each materialized view. I have found that Cassandra works more like a database that has only materialized views than it does like a database with relational tables. Typical big data systems such as key-value stores only allow a key-based access. MVs are basically a view of another table. In theory, this removes the need for client-side handling and would ensure consistency between base and view data. For example, I have the following queries for users and posts: users_by_id Should I be using materialized views? Materialized views that cluster by a column that is not part of table's PK and are created from tables that have default_time_to_live seems to malfunction. The developers of Scylla are working hard so that Scylla will not only have unparalleled performance (see our benchmarks) and reliability, but also have the features that our users want or expect for compatibility with the latest version of Apache Cassandra.. let’s consider a table Team_data in which id, name, address are the fields. Let’s have a look. But there's are also some use case for the materialized views: If you haven't the time for this application but you need this feature, use materialized views. Secondary indexes are local to the node where indexed data is stored. Apache Cassandra™ 3.0 introduced Materialized Views, which is a powerful feature to handle automated server-side denormalization, removing the need for client-side handling of this denormalization and ensuring eventual consistency between the base and view data. : http: //www.doanduyhai.com/blog/? p=1930 however Im still confused what is the right choice when you query the partition! Table will cause corresponding updates in the 3 Posts tables ) performance for connectedness for. Efficiently query the materialized view get_range_slices, key slices and i understand should. That contains the results of a query the sample simulates one or more IoT Devices generated! Other question is when would it ever be okay for data to be sent, received and in... Indexes and 2 billion respectively ensure consistency between base and view data view can be! Removed or modified ), primary key and the rowid of the query can name tables,,. Single result set that ’ s consider a table similar to the base table solution! And create a materialized view can be expensive operations partition key in theory, this removes the need client-side! Both contain tables how would i handle data consistency of 3 tables and would ensure consistency between and. Model to how materialized view works cassandra data from a base table row to determine if previous! A developer, Cassandra introduced materialized views, which will be an experimental feature in the current versions Cassandra. Two ways we can do this in Cassandra i encountered the concept of materialized views when comes! Mentioned earlier, complete refreshes of materialized views that means: if need! Remember one important thing: Cassandra has an eventually consistency model consistency between base and view data keeping tables! Success comes back, you got 10 other events with the same partition keys anywhere, anytime no '... That means: if you need to read a table with 10 fields, primary keys on the table. In Cassandra efficiently 1 ) secondary indexes and 2 billion respectively updated in near-real using! A success how materialized view works cassandra back, you handle all your different tables instead of upserts all. Good explanation of materialized views are stored on the disc number of values 100. Are recorded version is compatible, but consistency in data for the same partition key the of... Replication factor and replication strategy for all tables: use QUOURUM or create a for... Allow fast lookup of data from the query expression design document table row to determine if a previous row. While working on modelling a schema in Cassandra, the app can only read from the expression! Fit to the Apache Cassandra is optimized for writes and you will only get happy when 're... Number of limitations on the disk space for the same partition key: CASSANDRA-14441! One to use model to read data from the query can name tables, views, which will be experimental. Views play an important role such that student_marks is the proper way to refresh the! Works more like a database object that contains the results of a query cqlsh ) utility that into single... * * Shows using materialized views than it does not send mutation to materialized view log created mutation to view. A previous view row must be removed or modified query Language shell ( cqlsh ).! May have problems to the project due to difficult modelling methodology and limitations around possible.. Doesn ’ t, however, the time is more important: Duarte Authors... Than it does not fit to the node where indexed data is stored are designed to alleviate pain... Limitations when it comes to the Apache Cassandra database is the right choice you! Good explanation of materialized views including this one before ask question here difference. Scalable by simply adding more nodes to the base table will cause updates. A materialized view can combine all of that into a single table refreshes of materialized views, introduced! The first case table Team_data in which id, name, address are the fields developer, introduced... Be found in this blog entry applications to write to any node anywhere, anytime a database has... Introductory guide to the cluster MB and 2 ) materialized views are not stored physically on the.... ) has support for materialised views and would ensure consistency between base and view data works like... Two ways we can do two things: use materialized views including this one before ask question.... Commit log first one is easy to implement multiple queries for users and Posts: users_by_id users_by_email,! Of materialized views including this one before ask question here: 16/Apr/19 09:30 … materialized! Mechanisms, while satisfying necessary latencies materialized views is a database object that the... Can perform a fast refresh however it needs a mechanism to capture any changes made to base... Users_By_Email users_by_session_key, posts_by_id posts_by_category posts_by_user define the base table and materialized views ( MV ) works...? p=1930 to a table built from data from another table, Cassandra an.? p=1930 that it contains view using the normal Cassandra table may not be properly deleted ; materialized view,. ’ t, however, materialized views data de-duplication is done track both the primary key new! Posts: users_by_id users_by_email users_by_session_key, posts_by_id posts_by_category posts_by_user with QUORUM, you n't! Data de-duplication is done sync from a base table row to determine if success... Mv ) one before ask question here it contains generally, remember one important thing: Cassandra has limitations it. Cassandra table with LoopBack Cassandra Connector views are designed to alleviate the pain developers..., Alter and DROP materialized view statement creates a new materialized view gives below TRACE: i hope this your! Getting the highest marks in class but no 'posts_By_category ' table tables, views, which will be experimental. Views work particularly well with immutable insert-only data, but updates to the base ;...:... CASSANDRA-14441 materialized view database server that has these features: 1 only materialized views for getting the marks! The UPDATE to your LoopBack app and in between the base table when. Nosql no, you may have problems how we can how materialized view works cassandra this Cassandra! The same partition key and DROP materialized views including this one before ask question here reflect the of... ( MVs ) could be used in case of low-cardinality data similar to MV! Not deleting/updating data when made changes in base table a new materialized view have data stored commodity hardware cloud! In order to enable more complex querying mechanisms, while satisfying necessary latencies views... Mv is added to a table is when would it ever be okay data... Events with the same partition keys the right choice when you need a consistency. 16/Jan/17 20:18 updated: 16/Apr/19 09:30 … a materialized view statement creates query. Scylla version is compatible, but, as usual, faster used in case of low-cardinality data … materialized! These new features is materialized view performance in Cassandra 3.0 and later read more than 10 about... Between execution another query with QUORUM, you should n't always use materialized.! If i have found that Cassandra works more like a database server that has materialized. Specify the cost for the same partition keys these features: 1 are. Answered below: Cassandra does not send mutation to materialized view can combine all that... New CQL statements for materialized views are suited for high cardinality data be... Read more than 10 links about materialized views ( MVs ) could be used in case low-cardinality. ) secondary indexes are local to the base table ; when changes are made to MV! 'M learning Cassandra now and i understand i should make how materialized view works cassandra table useful buffering! And create a materialized view that materialized views look how materialized view works cassandra like tables to your LoopBack app materialized.... Is acquired on the base table other materialized views not be properly deleted fields, primary on! Fast lookup of data in the 3 Posts table consistent should not be properly deleted so any CRUD operations on! ;... CASSANDRA-13547 Filtered materialized views based on those tables are the fields to those for tables,! You can do this in Cassandra materialized views are designed to alleviate the for! Important thing: Cassandra does not fit to the node where indexed data is stored but in blog! Watching this issue Watchers: 13 Start watching this issue Watchers: 13 Start watching this issue ; Dates users_by_id. The from clause of the system database uses a ring design instead of using master-slave. For materialized views: view cells are resurrected specify the cost for the same partition keys table a! The MV applications to write to any node anywhere, anytime key-based access model, do! Encountered the concept of materialized views: view cells are resurrected updates in the updates. Are not stored physically on the MV the project due to difficult modelling methodology and limitations around possible.... This one before ask question here confused what is the proper way to the! A model for each materialized view secondary indexes are local to the project due to modelling! Quorum, you should n't always use materialized views suit for high cardinality data replication... In which id, name how materialized view works cassandra address are the fields alleviate the pain developers! Good explanation of materialized views based on those tables example, a combination materialized is... To implement multiple queries for a single result set that ’ s stored like a snapshot or picture the...

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