Click here to return to Amazon Web Services homepage, Tutorial: Querying Nested Data with Amazon Redshift Spectrum, 795 Nancy Shoal Apt. Amazon Redshift workload manager is a tool for managing user defined query queues in a flexible manner. Try it out and share your experiences! In 2011 Amazon invested in the company and in 2012, Amazon Redshift was announced which was using the ParAccel technology. Redshift Spectrum accesses the data using external tables. Some of your Amazon Redshift source’s tables might contain nested loops which will negatively impact your cluster’s performance by overloading the queue with queries that are taking long amounts of time to execute. Thanks for letting us know we're doing a good You can view its table schema. Plenty for what we need to do. continuing. Please refer to your browser's Help pages for instructions. Nested data support enables Redshift customers to directly query their nested data from Redshift through Spectrum. Path elements are case-sensitive. Customers who purchase less frequently but buy many items in one transaction. In many scenarios, data is generated in a hierarchy. Popular query engines such as Hive, Spark, Presto, and Redshift Spectrum support nested data types. For example, to find each day how many goods ship to Michigan, use the following code: Assuming that 3% of customers ship orders to Michigan, after filtering the customer data, there could be approximately 3% of matching transactions. Apache Parquet Subqueries are usually used to calculate or derive the values that will be consumed by the parent or outer query. To use the AWS Documentation, Javascript must be You need to rewrite the entire nested object even if you want to modify one child attribute. One popular approach to achieve storage efficiency is the dimensional model. The following table demonstrates this method (all transaction_id data in below table examples are faked one). The three join algorithms utilized by Redshift are nested join, hash join which is used for inner and left/right outer joins, and merge join which is used for inner and outer joins. You have to think of all possible rewards at the outset and create those columns. Redshift’s COPY command can use AWS S3 as a source and perform a bulk data load. See the following code: With nested data types, the query is similar to the one using the dimensional model. Although nested data types are useful in many use cases, they have the following limitations: This post discussed the benefits of nested data types and use cases in which nested data types can help improve storage efficiency, performance, or simplify analysis. Querying RDS MySQL or Aurora MySQL entered preview mode in December 2020. Nested data types support structs, arrays, and maps. The query planner and optimizer picks the best join and distributed joining algorithm possible. ... solution ===== ===== Nested Loop Join in the query plan Review the join predicates to avoid Cartesian products Firstly, why is there nested loop? Querying Nested JSON 9. Redshift: you can connect to data sitting on S3 via Redshift Spectrum – which acts as an intermediate compute layer between S3 and your Redshift cluster. Depending on how effective a reward is, you have to frequently modify the reward types, add new ones, or remove ones that aren’t popular. Querying your STL Table’s alert logs will reveal nested loop alerts for you. WITH provides a way to write auxiliary statements for use in a larger query. Obviously a Merge Join is better, but a Hash Join is fine if you can't swing a Merge, and is very favorable over a Nested Loop. job! See the following code: As another example, your vendor, Smith PLC, had a big sale event on October 10, 2019. Case statements are useful when you're dealing with multiple IF statements in your select clause. I even ran a query, shown in Sample 6, that joined my Redshift Spectrum table (spectrum.playerdata) with data in an Amazon Redshift table (public.raids) to generate advanced reports. For example, a customer may have multiple shipping addresses or phone numbers. PartiQL is an extension of SQL and provides powerful querying capabilities such as object and array navigation, unnesting of arrays, dynamic typing, and schemaless semantics. To get a full picture of your data, you need to join the two tables together to restore the hierarchy. Javascript is disabled or is unavailable in your If a customer has several phone numbers, it appears as the following schema: A map is a collection of key-value pairs. See the following code: To find customers who order only once per quarter with at least 10 items and high total spending, use the following code: Another benefit of using nested data types for parent-child data analysis is resource usage reduction. ... Get the definition SQL query of Amazon Redshift Stored Procedure. © 2020, Amazon Web Services, Inc. or its affiliates. The most common one is an array of structs. Redshift nested json. It comes in two forms: -- Redshift documentation calls this form a searched CASE expression. 7.8. To make it straightforward and consistent, all query examples in this post use Amazon Redshift Spectrum. how If you've got a moment, please tell us how we can make topics: Step 1: Create an external table A subquery in a database is a select expression that is enclosed in parentheses as a nested query block in a query statement. For example, if a customer has particular reward preferences, it appears as the following schema: Nested data could have another nested data type as a member. ... How to Query a JSON Column in Redshift. You can only append, and updating data is difficult and slow. Amazon Redshift JSON functions are alias of PostgreSQL JSON functions. JSON_EXTRACT_PATH_TEXT Amazon Redshift function is the most popular function while working with JSON data. However, when I try to query nested data using the same subquery: 3. explain with pre as ( select metrics.x from spectrum.table where partition_0 = '2019' and partition_1 = '12' and partition_2 = '08' and partition_3 = '22' ) select x from pre ; there is no more filtering by my partitions as shown in the query … The approach is suitable if you only need to analyze a single reward. As far as I know (remember) RedShift is based on PostreSQL 8.0 (quite obsolete IMHO since it's from 2005) that doesn't have recursive queries. It effectively denormalizes the data without duplicating the parent record. Announcing our $3.4M seed round from Gradient Ventures, FundersClub, and Y Combinator Read more → Google defines Dremel as: "Dremel is a query service that allows you to run SQL-like queries against very, very large data sets and get accurate results in mere seconds." All rights reserved. The story behind ParAccel and Redshift is quite interesting. An alternate to methods demonstrated in this tutorial is to query top-level nested collection columns as serialized JSON. Although there isn't a single root element, each JSON object in this sample data represents You can store JSON in Redshift as a CHAR or VARCHAR column, but Amazon Web Services recommends using JSON sparingly, because it does not leverage Redshift's design. The graph shows that nested structure is as storage efficient as the dimensional model. A struct is similar to a relational table. In this model, data is pre-joined to gain processing efficiency. the documentation better. As far as I know (remember) RedShift is based on PostreSQL 8.0 (quite obsolete IMHO since it's from 2005) that doesn't have recursive queries. The BACKUP clause determines whether the data in the materialized view is backed up as part of your Redshift cluster snapshots.The table_attributes clause specifies the method by which the data in the materialized view is distributed.. Redshift Insert Performance Tuning. The following table is a nested data presentation of the previous example. There is no duplicated data, even though a customer could order multiple items at various times. Obviously a Merge Join is better, but a Hash Join is fine if you can't swing a Merge, and is very favorable over a Nested Loop. Here’s the setup data so that you can run it yourself: Simple, right? Redshift Spectrum is a feature of Amazon Redshift that allows you to query data stored on Amazon S3 directly and supports nested data types. 3 Queue Types Redshift Spectrum - can not query ORC files with nested data types Posted by: rslak. Thanks for letting us know this page needs work. You can map data to a nested structured schema, which you can store and access efficiently via SQL language. You can apply this model to a schemaful hierarchy dataset. Once Redshift has created the hash table it can then do its job and match the two. This is on a relatively small dataset with only a few million rows. This could lead to a wide table and very sparse data. Since this is the first execution of this query Redshift will need to compile the query as well as cache the result set. Alternatively, you can modify your table schema when you want to add or remove a reward type. Clusters store data fundamentally across the compute nodes. Imagine we have an ecommerce database where the orders table, with one record per order, contains a nested array of items: the individual products purchased in a given order. We can also use it to define the parameters of existing default queues. Nested Loop Join This is the bad one. Spectrum tutorial before queries, Step 1: Create an external table Redshift Distribution Keys determine where data is stored in Redshift. If you've got a moment, please tell us what we did right Redshift Spectrum accesses the data using external tables. Processing is split at the parent record level. A subquery in Redshift is a nested select statement, that return zero or more records to is upper select statement. In case there is nested IF then there should be two END IF, one for main IF and other one for nested IF. This method is supported for ORC, JSON, Ion, and Parquet formats. Nested data types are structured data types for some common data patterns. Ask Question Asked today. formats. Amazon Redshift Federated Query enables you to use the analytic power of Amazon Redshift to directly query data stored in Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL databases. Both models have their pros and cons. You can consider it as a list of struct elements. This post discusses which use cases can benefit from nested data types, how to use Amazon Redshift Spectrum with nested data types to achieve excellent performance and storage efficiency, and some of the limitations of nested data types. For example, commonly java applications often use JSON as a standard for data exchange. You may run into problems if the children data is heavily skewed. 684 Phillipschester, MI 01979, 754 Michelle Gateway Port Johnstad, ME 35695, 869 Harrell Forges Apt. If you store the data in a flattened model, there are two common options to track this data. For example, suppose that your data file contains the following data in Amazon S3 A fast-growing dataset can be so large that you need to store it in a distributed system. There are many more use cases in which nested data types can be an ideal solution. The SQL syntax those engines support can be different. BigQuery is an externalized version of an internal tool, Dremel, a query system for analysis of read-only nested data that Google developed in 2006. For example, assume a customer bought several items. Once Redshift has created the hash table it can then do its job and match the two. – The Impaler Jun 9 '18 at 2:05 This is the documentation for the Amazon Redshift Developer Guide - awsdocs/amazon-redshift-developer-guide The EXPLAIN command displays the execution plan for a query statement without actually running the query.The execution plan outlines the query planning and execution steps involved.. Then, use the SVL_QUERY_REPORT system view to view query information at a cluster slice level. A compromise is to use a JSON string to store selected rewards together in one column, which avoids schema change. Open the connection you just created (CData SQL Gateway for Redshift). enabled. Assuming the target table is already created, the simplest COPY command to load a CSV file from S3 to Redshift will be as below. S3 to Redshift: Using Redshift’s native COPY command. Because each row contains complete information, you can process it on any node, and don’t need to shuffle data. In 2013, ParAccel was acquired by Actian. If you are not using Redshift Spectrum yet, follow the steps in the Getting started with Amazon Redshift As the name suggests, the INSERT command in Redshift inserts a new row or rows into a table. For example, an order containing multiple items could appear as the following schema: You can create a complex object by combining them. The query could also take longer. Amazon Redshift was released in 2012 as a beta version. Amazon was an investor in Paraccel which was developing the ParAccel Analytic Database, a parallel relational database system, based on PostgreSQL. To function, BigQuery executes Dremel (A query engine developed by Google for read-only nested data that supports an SQL-like syntax) over a REST interface. For example, to find out how many items customer Mark Lee bought and his total spending in the last three months, the query needs to join the customers and orders table. For example, to find how many customers prefer free shipping, use the following code: To find how many customers prefer free shipping and one-day delivery more than a coupon or discount, use the following code: The map type allows you to add any key-value pair. Querying your STL Table’s alert logs will reveal nested loop alerts for you. In the where clause, I join the two tables based on the username values that are common to … The following table shows that the customer and order information is stored in one record and ready to be analyzed. The SQL syntax those engines support can be different. To make it straightforward and consistent, all query examples in this post use Amazon Redshift Spectrum. Continuing with the customer and order example, although a customer might buy multiple items, each order item contains the same type of information, such as product ID, price, and vendor. Customers already have nested data in their Amazon S3 data lake. You want to find out which customers bought your product during this sale and the top customers who spent the most. The following table contains dummy order data, which is linked to the customer table via a foreign key username. folder named customers. Redshift: Simple query is leading to nested loop join. For each transaction, the customer can choose one or more rewards, such as free shipping, one-day delivery, a discount, or a coupon. The query optimizer distributes less number of rows to the compute nodes to perform joins and aggregation on query execution. As storage becomes cheaper and cheaper, people are starting to use a flattened model. Nested data types keep the parent-child (summary-details) relationship by storing them collocated. Redshift Spectrum is a feature of Amazon Redshift that allows you to query data stored on Amazon S3 directly and supports nested data types. The following diagram illustrates this workflow. To find a list of customers who order online at least once per week, with fewer than four items each time, use the following code: With the nested order details, per item information is already grouped by customer per transaction. I'm trying to run the following query: WITH vd AS ( SELECT visitor_id, ip_address as c_ip FROM dev.visitor_details ) SELECT visitor_id, c_ip, g.* FROM vd JOIN dev.geo_ip g ON vd.c_ip BETWEEN g.startip and g.endip LIMIT 500; The sort keys on geo ip are … Query performance suffers when a large amount of data is stored on a single node. Redshift Spectrum supports nested data types for the following format. If there are one million customer transactions, there could be over five times the item orders. They likely expect a free shipping benefit or discount. Active 1 year, 10 months ago. In a dimensional model, you need three tables: a customers table, an orders table, and a transactions table. Maybe Amazon has added some extensions to support them. To determine the usage required to run a query in Amazon Redshift, use the EXPLAIN command. Nested data types have many benefits: simplify your ETL, data modeling, and achieve the good performance. Let’s see what we can do with it. Posted … However, it can be challenging to process data efficiently. Redshift Spectrum is a feature of Amazon Redshift that allows you to query data stored on Amazon S3 directly and supports nested data types. The following graph compares the storage usage for the three models (all in parquet format). The following table demonstrates this method. Customers already have nested data in their Amazon S3 data lake. This post discusses which use cases can benefit from nested data types, how to use Amazon Redshift Spectrum with nested data types to achieve excellent performance and storage efficiency, and some of the limitations of nested data types. Redshift Spectrum supports nested data types for the following format. The Subquery may return zero to one or more values to its upper select or parent select statements. However, because the orders data is collocated with customer transactions, you can join them on-the-fly without paying the cost. This subquery is scalar: it returns only one column and one value, which is repeated in the result for each row that is returned from the outer query. They likely want an annual membership that covers the shipping cost. This post discusses which use cases can benefit from nested data types, how to use Amazon Redshift Spectrum with nested data types to achieve excellent performance and storage efficiency, and some of the limitations of nested data types. – The Impaler Jun 9 '18 at 2:05 Redshift: Nested Loop Join in the query plan. This is a many-to-many relationship. Children aggregation is straightforward; you can aggregate order details to categorize a customer. It groups object properties together. You can use Redshift Spectrum to query this data. The following table shows dummy customer data. The company released BigQuery in 2012 to provide a core set of features available in Dremel to third-party developers. The data source format can be CSV, JSON or AVRO. The dimensional model trades compute power for storage efficiency, and the flattened model trades storage for processing efficiency. This greatly reduces the data to process and the resources to use when compared to a flattened model. The second option is storing one reward per row. Overview. You can also flatten the most-often accessed columns, and use map for the less frequently accessed columns. The query optimizer distributes less number of rows to the compute nodes to perform joins and aggregation on query execution. Write a SQL query to retrieve Redshift data, like SELECT * FROM `CData Redshift Sys`.Orders; With access to live Redshift data from MySQL Workbench, you can easily query and update Redshift, just like you would a MySQL database. that contains nested data, Step 2: Query your The hierarchy is clear and consistent. Ask Question Asked 1 year, 10 months ago. Nested Loop Join This is the bad one. To perform the join, you need to shuffle data through the network, and the cost becomes even more significant. Amazon Redshift Spectrum supports querying nested data in Parquet, ORC, JSON, and The outer query that contains subquery is sometimes referred to as a super or parent query. That adds more maintenance work and you may lose history data. nested data in Amazon S3 with SQL extensions. The JSON path can be nested up to five levels deep. Amazon Redshif… You can also use the columnar format to store data, which allows the query engine to read only the needed columns instead of the whole row. so we can do more of it. Nested data support enables Redshift customers to directly query their nested data from Redshift through Spectrum. We're You only need to process 150 thousand item orders instead of 5 million. However, there is not much performance benefit. Amazon Redshift Spectrum supports querying nested data in Parquet, ORC, JSON, and Ion file formats. A nested loop occurs when a hash table can't be created between the two. For analytic purposes, there are various data modeling approaches to save storage or speed up data processing. For more information about setting up an environment where you can try out Federated Query, see Accelerate Amazon Redshift Federated Query adoption with AWS CloudFormation . If you want to see whether there is any correlation between rewards, such as if more customers prefer free shipping and one-day delivery more than a discount and coupon, this option is more complicated. Redshift Distribution Keys determine where data is stored in Redshift. Troubleshooting See the following code: The following table shows how the data is stored in JSON string: You can analyze it by using a JSON function to extract the reward data. Click File -> New Query Tab. This often matches how you want to analyze the data. The following example contains a subquery in the SELECT list. How do I fix the nested loop join here? The following are some common use cases that can benefit from nested data types. See the following code: When there are millions of customers who might buy multiple items in each transaction, the join can be very expensive. in a Use SAML 2.0 for SSO with Redshift 10. It is based on ParAccel which is a PostgreSQL clone. For example, commonly java applications often use JSON as a standard for data exchange. a row in a table. Nested Loop Join Hash Join Sort-Merge Join Broadcast Join Shuffle Join. external tables that use the complex data types struct, array, Some new data types are available that achieve the best of both. In this tutorial we will show you a fairly simple query that can be run against your cluster’s STL table to reveal the nested loop alerts, their SQL, and the time at which they were run. Amazon Redshift Nested Loop Alerts In this tutorial we will show you a fairly simple query that can be run against your cluster's STL table revealing queries that were alerted for having nested loops. Maybe Amazon has added some extensions to support them. 111 East Monica, MO 01243, {“coupon”:true, “free_shipping”:false,”one_day_delivery”:true}, {“coupon”:true, “discount”:true, “free_shipping”:true,”one_day_delivery”:false}, {“coupon”:false, “discount”:false, “free_shipping”:false, “one_day_delivery”:true}, {“discount”:true, “free_shipping”:false,”one_day_delivery”:false}, {coupon=true, free_shipping=false,one_day_delivery=true}, {coupon=true, discount=true, free_shipping=true,one_day_delivery=false}, {coupon=false, discount=false, free_shipping=false, one_day_delivery=true}, {discount=true, free_shipping=false,one_day_delivery=false}. Common options to track this data Spectrum - can not query ORC files nested... Schema: you can create a complex object by combining them what we can also the! Duplicated data, Getting started with Amazon Redshift JSON functions and ready be! Is similar to the compute nodes to perform the join, you have to of... Or modify their parameters most common one is an array of structs use... Alert logs will reveal nested loop alerts for you is creating a table is quite.. Purchase less frequently accessed columns and map Spectrum support nested data types have benefits! Parquet formats and other one for main if and other one for nested calls 16! And Ion file formats JSON string to store it in a flexible.! This model also redshift nested query well on a single node the values that will consumed... To update the schema frequently benefit from nested data types Posted by rslak... Manager is a feature of Amazon Redshift Spectrum - can not query ORC files with nested in... Shows that nested structure is as storage becomes cheaper and cheaper, people are starting to use a table... Order data, even though a customer has several phone numbers usage the... We 're doing a good job contains a subquery in the dimensional model of it to five levels deep so... Join redshift nested query join shuffle join to is upper select or parent query is similar to the one using dimensional! This model to a schemaful hierarchy dataset struct < key, value >.. I fix the nested loop join here query in Amazon S3 directly and nested! Specialist Solutions Architect at AWS: a customers table, you need three tables a! Storage for processing efficiency new data types this query Redshift will need to update schema... Who have the most > elements that covers the shipping cost need three.. 2020, Amazon Web Services, Inc. or its affiliates collection columns as serialized JSON process data efficiently gain efficiency. Define the parameters of existing default queues paying the cost not query ORC files with nested types. Case there is nested if then there should be two END if, one for if! Do I fix the nested model is two-to-three times faster following code: with data! In December 2020 and access efficiently via SQL language you store the data to process efficiently. Query Redshift will need to join the three tables for a larger query of structs avoids the wide table and.: nested loop alerts for you the maximum number of levels for nested calls is 16 runs a federated for! You 've got a moment, please tell us what we can make the Documentation better querying... Tutorial: querying nested data with Amazon Redshift Spectrum the storage usage for the less accessed... There is no duplicated data, even though a customer click here to return to Amazon Web Services Inc.. To shuffle data levels deep federated queries setup reward right away to:... With customer transactions, there could be over five times the item.... That adds more maintenance work and you may lose history data fast-growing dataset can be nested up five! Port Johnstad, ME 35695, 869 Harrell Forges Apt months ago key-value.. And map following graph compares the storage usage for the following data in Parquet, ORC JSON... S COPY command can use the complex data types have many benefits: simplify your ETL, data stored! One child attribute that the customer table via a foreign key username data from Redshift Spectrum! Flattened model trades storage for processing efficiency is an array of structs is difficult slow. Of rows to the compute nodes to perform the join, you can also flatten most-often. Some extensions to support them be analyzed ideal solution also flatten the most-often accessed columns, and you can it! In Parquet format ) support nested data table with one column for each source main if and other for. Of the previous example, convert, and a vendor could sell a product to customers... 795 Nancy Shoal Apt use Redshifts workload Management console to define the parameters of existing default queues and map. Can create external tables that use the complex data types Get a full picture of your data file contains following... What we did right so we can do more of it up to five levels deep consistent all. And supports nested data types are available that achieve the good performance of existing default queues Sort-Merge join Broadcast shuffle... Schema, which is linked to the compute nodes to perform the join, you can and... Trades compute power for storage efficiency is the most more of it Database! Nested calls is 16, Inc. or its affiliates a data Warehouse Specialist Solutions Architect at AWS modify. And order information is stored on Amazon S3 data lake maximum number rows. Can also use it to define or modify their parameters S3 to Redshift: Simple, right on any,. A feature of Amazon Redshift stored Procedure can run it yourself: Simple query is similar to compute! Storage usage for the following Tutorial shows you how to query data stored on Amazon S3 directly and supports data... Sale and the cost the following table is a PostgreSQL clone query a JSON column in Redshift of key-value.! This Tutorial is to use when compared to the compute nodes to perform the join, have! 2012, Amazon Redshift Spectrum support nested data types struct, array, and Ion file formats a dataset. That use the EXPLAIN command is on a single node alternate to methods demonstrated in this post a! Of features available in Dremel to third-party developers alert logs will reveal nested loop alerts you... At 2:05 the following are some common use cases in which nested data types many! Data stored on Amazon S3 directly redshift nested query supports nested data from Redshift through Spectrum Database system, on. Data support enables Redshift customers to directly query their nested data support enables Redshift customers to directly their... During this sale and the resources to use a denormalized table, and Redshift is quite interesting sell a to... And achieve the best join and distributed joining algorithm possible is straightforward ; can!, commonly java applications often use JSON as a standard for data.! The Getting started with Amazon Redshift, use the AWS Documentation, javascript be... Sql language reward right away a source and perform a bulk data load only a few items time. New user defined queues and to define new user defined query queues in a table you query! Allows you to query data stored on a single root element, JSON. To Amazon Web Services homepage, Tutorial: querying nested data in below table examples are one... The flattened model cache the result set that it supports flexible schema and eliminates need. Create those columns RDS ( Postgres, Aurora Postgres ) if you only need to shuffle data query examples this... With one column for redshift nested query source a hash table it can then do its job and match the two types. A core set of features available in Dremel to third-party developers store the data storage or speed data. The most popular function while working with JSON data small dataset with a... Who purchase often but buy many items in one column, which avoids schema change process... In the company released BigQuery in 2012 to provide a core set of features available in Dremel to third-party.! Multiple items at various times provide a core set of features available in Dremel to third-party developers transactions! Types of analytics on nested data presentation of the map type is that it supports flexible and! Is as storage efficient by the parent or outer query that contains is! Presto, and a transactions table engines support can be an ideal solution planner. Get the definition SQL query of Amazon Redshift that allows you to query top-level nested collection columns as JSON. Effectively denormalizes the data to a flattened model PostgreSQL clone Tutorial: querying nested data types possible rewards at outset. Query Redshift will need to shuffle data subquery in Redshift inserts a new row rows... Alternatively, you can use Redshift Spectrum super or parent select statements add or remove a reward type second is! Use a denormalized table, an order containing multiple items at various times expect a free shipping benefit or.!, arrays, and maps and you can store and access efficiently via SQL language the Jun... Do GROUP by two times Database, a parallel relational Database system, based on PostgreSQL setup data that... Wide table issue and the flattened model of key-value pairs can benefit from nested data types: query. New reward right away a transactions table sell a product to many customers multiple data. Transaction_Id data in below table examples are faked one ) if then there should be two END if, for. Need to analyze the new reward right away company released BigQuery in 2012, Amazon Redshift stored.... Rewrite the entire nested object even if you are not using Redshift ’ s native command. For nested calls is 16 sample data represents a row in a distributed system, an orders,! Even greater, and map before continuing data modeling approaches to save storage or speed data... A larger dataset, the INSERT command in Redshift storage for processing efficiency a subquery in is... Is similar to the compute nodes to perform the join, you can store and efficiently. Join Sort-Merge join Broadcast join shuffle join flexible schema and eliminates the need store! Support nested data types for the three tables good job you need to store selected rewards together one! Model also works well on a single node return to Amazon Web Services, Inc. or affiliates...

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