Amazon Redshift Few people will deny that Presto works well when generating frequent reports. It does matter to plenty of people, but others will just shrug. , which means it filters and sorts tasks while managing them on distributed servers. Presto relies on standard SQL to executive queries, retrieve data, and modify data in databases. Professionals who know how to code can write custom commands for their projects. Hive is query engine that whereas HBase is a data storage particularly for unstructured data. data from many different data sources into Redshift. Through this summary of the differences between Hive and MySQL, I hope I’ve helped provide some direction on which platform to … It allows for querying data stored on HDFS for analysis via HQL, an SQL-like language that gets translated to MapReduce jobs. If you have a fact-dim join, presto is great..however for fact-fact joins presto is not the solution.. Presto is a great replacement for … etl. Even with that solution, users waste precious time tracking down the failure’s source and diagnosing the issue. Since it data doesn’t get locked into one place, Presto can run tasks without stopping to write data to the disk. You can reach a limit, though. In this difference between the Internal and External tables article, you have learned internal/managed tables metadata and files are owned Hive server and manages complete table life cycle whereas only metadata is owned by external tables meaning dropping an external table just drops it’s metadata but not the actual file and also learned when to use internal table vs external table. As nouns the difference between hive and beehive is that hive is a structure for housing a swarm of honeybees while beehive is an enclosed structure in which some species of honey bees (genus apis ) live and raise their young. How Hive Works Hive translates SQL queries into multiple stages of MapReduce and it Now in the next section of our post, we will see a functional description of these SQL query engines and in the next section, we would cover the difference between these engines as per their properties. FIND OUT IF WE CAN INTEGRATE YOUR DATA Aggregate, Group by, Fact-Dim join type of queries) Just because some people prefer Hive, doesn’t necessarily mean that you should discount Presto. Both Apache Hive and HBase are Hadoop based Big Data technologies which are basically serve the same purpose to query the Big Data. From a user’s perspective, Presto is designed for interactive queries, whereas Hive was designed for batch processing. Presto can handle limited amounts of data, so it’s better to use Hive when generating large reports. Difference between Pig and Hive : S.No. Key Differences Between Spark SQL and Presto. One of the first things that many data engineers notice when they first try Presto is that they can use their existing SQL knowledge. A Big Data stack isn’t like a traditional stack. Hive uses map-reduce architecture and writes data to disk while Presto uses HDFS architecture without map-reduce. Xplenty has helped us do that quickly and easily. Below is the list, about the key difference between Presto and Spark SQL: Apache Spark introduces a programming module for processing structured data called Spark SQL. Hive can often tolerate failures, but Presto does not. select * from table1 limit 10; Not surprisingly, though, you can encounter challenges with the architecture. Presto was later designed to further scale operations and reduce query time. But before going directly into hive and HB… Customer Story If you don’t have an extensive technical background, Presto vs Hive may seem like a moot argument. However, Apache Hive and HBase both run on top of Hadoop still they differ in their functionality. Structure can be projected onto data already in storage; Presto: Distributed SQL Query Engine for Big Data. Presto began as a Facebook project that would let engineers run interactive analytic queries against the company’s huge (300PB) data warehouse. The data files themselves can be of different formats and typically are stored in an HDFS or S3-type system. Differences between Apache Hive and Apache Spark. Facebook released Presto as an open-source tool under Apache Software. Copyright © 2020 Treasure Data, Inc. (or its affiliates). I don’t know Presto but the reason I’m responding is that Presto and PostgreSQL are usually the references for SQL support in Spark SQL (the ANTLR grammar for SQL was borrowed from Presto I believe). There is much discussion in the industry about analytic engines and, specifically, which engines best meet various analytic needs. The inability to insert custom code, however, can create problems for advanced big data users. MapReduce also helps Hive keep working even when it encounters data failures. After abandoning it in favor of Presto, Hive also became an open-source Apache tool data warehouse tool. Many of our customers issue thousands of Hive queries to our service on a daily basis. (HDFS), a non-relational source that does not have to write data to the disk between tasks. MapReduce is fault-tolerant since it stores the intermediate results into disks and enables batch-style data processing. The loss of third-party cookies does not mean the end of exceptional omnichannel experiences. Hive Hbase Database. Pig operates on the client side of a cluster. Just don’t ask it to do too much at once. It’s intuitive, it’s easy to deal with [...] and when it gets a little too confusing for us, [Xplenty’s customer support team] will work for an entire day sometimes on just trying to help us solve our problem, and. Hive operates on the server side of a cluster. Treasure Data Customer Data Platform (CDP) brings all your enterprise data together for a single, actionable view of your customer. Before taking the time to write custom code in HiveQL. Presto Hive typically means Presto with the Hive connector. Apache maintains a comprehensive language manual for HiveQL, so you can always look up commands when you forget them. MapReduce works well in Hive because it can process tasks on multiple servers. But there are some differences between Hive and Impala – SQL war in the Hadoop Ecosystem. Hive lets users plugin custom code while Preso does not. Usage: – Hive is a distributed data warehouse platform which can store the data in form of tables like relational databases whereas Spark is an analytical platform which is used to perform complex data analytics on big data. So, in this blog “HBase vs Hive”, we will understand the difference between Hive and HBase. Before creating. Before Hive 3.1, Hive would always (?) Keith connected multiple data sources with Amazon Redshift to transform, organize and analyze their customer data. RDBMS Architecture. Failures only happen when a logical error occurs in the data pipeline. TRUSTED BY COMPANIES WORLDWIDE. Presto supports. Anyone familiar with SQL, though, should find that they can pick up HiveQL relatively quickly. If you do, you run the risk of failure. big data, what types of records are found in the table), Large distincts (aka de-duplication jobs), Joins with a large Fact table and many smaller Dimension tables, HiveQL (subset of common data warehousing SQL), Optimized for star schema joins (1 large Fact table and many smaller dimension tables). If you want a straightforward ETL solution that works well for practically every member of your organization. Some popular ones include: The 5 biggest differences between Presto and Hive are: Customer Story Hive doesn’t seem to have a data limitation, at least not one that will affect real-world scenarios. In this case, Hive offers an advantage over Presto. Since it data doesn’t get locked into one place, Presto can run tasks without stopping to write data to the disk. It’s intuitive, it’s easy to deal with [...] and when it gets a little too confusing for us, [Xplenty’s customer support team] will work for an entire day sometimes on just trying to help us solve our problem, and they never give up until it’s solved. Apache Hive was open sourced 2008, again by Facebook. All rights reserved. If you cannot find the specific code that you need, you may find a plugin that only needs small changes to perform your unique command. Today, companies working with big data often have strong preferences between Presto and Hive. HiveQL, which stands for Hive Query Language, has some oddities that may confuse new users. The ETL solution has a no-code and low-code platform. MongoDB Presto supports Hadoop Distributed File System (HDFS), a non-relational source that does not have to write data to the disk between tasks. Apache Hive is a data warehouse infrastructure built on top of Hadoop. Pig uses pig-latin language. When something goes wrong, Presto tends to lose its way and shut down. Still, looking up the information creates a distraction and slows efficiency. . Presto is an in-memory distributed SQL query engine developed by Facebook that has been open-sourced since November 2013. Presto is much faster for this. Difference Between Hive Internal and External Tables. Assuming that you know the language well, you can insert custom code into your queries. Both Apache Hiveand Impala, used for running queries on HDFS. Presto processes tasks quickly. I have a Hive DB - I created a table, compatible to Parquet file type. Such error handling logic (or a lack thereof) is acceptable for interactive queries; however, for daily/weekly reports that must run reliably, it is ill-suited. Druid and Presto are both open source tools. Once you see how easy it works for everyone, you will wonder why you ever worried about choosing between Presto and Hive. In terms of data-processing models, Hive is often described as a pull model, since its MapReduce stage pulls data from the preceding tasks. Presto has a different architecture that makes gives makes it useful on some occasions and troublesome on others. We use cookies to store information on your computer. Xplenty’s platform alerts users when these issues happen, so you can fix them easily. Senior Developer at Creative Anvil Before we started with Xplenty, we were trying to move data from many different data sources into Redshift. Keep in mind that Facebook uses Presto, and that company generates enormous amounts of data. The connector allows querying of data that is stored in a Hive data warehouse. If you are not happy with the use of these cookies, please review our cookie policy to learn how they can be disabled. HDFS doesn’t tolerate failures as well as MapReduce. Before we started with Xplenty, we were trying to move, They really have provided an interface to this world of data transformation that works. first_page Previous. Difference between Hive and Cassandra. Presto has a limitation on the maximum amount of memory that each task in a query can store, so if a query requires a large amount of memory, the query simply fails. How useful are polls and predictions? Not sure why this would happen since both Presto-EMR and Athena are using the same Glue catalog. Ensuring Exceptional Customer Experiences—Even Without 3rd-Party Cookies. The Magic of Presto: Petabyte Scale SQL Queries in Seconds, Treasure Data Customer Data Platform (CDP), Six Ways Your Brand Can Connect with Customers in the Current Crisis, The 10 Best Coronavirus Data Visualizations We’ve Found, High Performance SQL: AWS Graviton2 Benchmarks with Presto and Arm Treasure Data CDP, Shifting Customer Journeys with Customer Data Enrichment: A Marketer’s Guide, Lessons Learned WFH—5 Tips to Make It Work for You, New Study Finds Data Key to Unlocking Superior Customer Experience, Frost and Sullivan Names Arm Treasure Data ‘Global Company of the Year’ in CDPs, Interactive queries (where you want to wait for the answer), Quickly exploring the data (e.g. "Real Time Aggregations" is the primary reason why developers consider Druid over the competitors, whereas "Works directly on files in s3 (no ETL)" was stated as the key factor in picking Presto. A close comparison shows that the options have some similarities and differences, but neither has the comprehensive features needed to manage and transform big data. Still curious about Presto? By disabling cookies, some features of the site will not work. TRUSTED BY COMPANIES WORLDWIDE. One thing to note is that Hive also has its own query execution engine, so there’s a difference between running a Presto query against a Hive-defined table and running the same query directly though the Hive CLI. A math nerd turned software engineer turned developer marketer, he enjoys postmodern literature, statistics, and a good cup of coffee. You don’t know enough SQL to write custom code, so why would that matter to you? Difference Between MapReduce and Hive. Presto would use these classes only when using Hive SerDe directly, so not in case of ORC, Parquet, RCFiles which all have dedicated reader implementations. Presto is designed to comply with ANSI SQL, while Hive uses HiveQL. RDBMS Full Form. Still, looking up the information creates a distraction and slows efficiency. Hive uses HiveQL language. Instead, it’s an opportunity for the industry to move toward a fully connected ecosystem, with an identity-based infrastructure at the core. The difference between the two is that the data in Google Maps is owned by Google, and OSM data is free to use (as long as anything derived from it is also free to use). Apache Hive is mainly used for batch processing i.e. One of the first things that many data engineers notice when they first try Presto is that they can use their existing SQL knowledge. Conclusion. We delve into the data science behind the US election. As a verb hive is (entomology) to enter or possess a hive. PRESTO FEATURES 5x-20x faster compared to Hive Works really well with ORC Near 100% compliant with ANSI SQL Parquet related enhancements are in works Good tool for interactive discovery - (e.g. Difference Between Hive, Spark, Impala and Presto Presto relies on. Beehive is a derived term of hive. Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. Hive translates SQL queries into multiple stages of MapReduce and it is powerful enough to handle huge numbers of jobs (Although as Arun C Murthy pointed out, modern Hive runs on Tez whose computational model is similar to Spark’s). The more data involved, the longer the project will take. Both Apache Hive and HBase are Hadoop based Big Data technologies. Apache Hive is designed to facilitate analytics on large amounts of data, while also providing storage for the results in the form of tables. 3. Presto can handle limited amounts of data, so it’s better to use Hive when generating large reports. Many people see that as an advantage. If you cannot find the specific code that you need, you may find a plugin that only needs small changes to perform your unique command. Instead, HDFS architecture stores data throughout a distributed system. Anyone familiar with SQL, though, should find that they can pick up HiveQL relatively quickly. Does Presto Use Spark? If you generate hourly or daily reports, you can almost certainly rely on Presto to do the job well. Pig is a Procedural Data Flow Language. and search for a similar code. The Differences Between PrestoSQL, PrestoDB and Trino. 01, Jan 21. 08, Jun 20. favorite_border Like. Pig Hive; 1. Hive vs. HBase - Difference between Hive and HBase. Xplenty builds a bridge between people who have and do not have strong technical backgrounds. uses a language similar to SQL, but it has enough differences that beginning users need to relearn some queries. to executive queries, retrieve data, and modify data in databases. Xplenty also helps solve the data failure issue. It will keep working until it reaches the end of your commands. It doesn’t happen often, but you can lose hours of work from a failure. Presto has a limitation on the maximum amount of memory that each task in a query can store, so if a query requires a large amount of memory, the query simply fails. Someone may have already written the code that you need for your project. Once you see how easy it works for everyone, you will wonder why you ever worried about choosing between Presto and Hive. 4. 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Presto began as a Facebook project that would let engineers run interactive analytic queries against the company’s huge (300PB) data warehouse. Presto is designed to comply with ANSI SQL, while Hive uses HiveQL. Amazon Redshift Dave Schuman It can extract multiple data formats from several databases simultaneously. Did you miss the Gartner Marketing Symposium? Presto has been adopted at Treasure Data for its usability and performance. Learn how Treasure Data customers can utilize the power of distributed query engines without any configuration or maintenance of complex cluster systems. The best feature of the platform is having the ability to manipulate data as needed without the process being overly complex. Furthermore, Hive itself is becoming faster as a result of the Hortonworks Stinger initiative. March 20, 2015, Key Takeaways from 2020 and the Gartner Marketing Symposium. Xplenty helps 1000s of customers cut weeks of development time with out-of-the box integrations that connect 100s of popular data sources and SaaS applications. Also, both serve the same purpose that is to query data. Since Presto runs on standard SQL, you already have all of the commands that you need. HBase is a completely different game it allows Hadoop to support lookups/transactions on key/value pairs. The 5 biggest differences between Presto and Hive are: Hive lets users plugin custom code while Preso does not. Apache Hive and Presto both enable organizations to perform queries on business data, but they also have some standout features that set them apart from each other. You can open Hive and run a query and sit and wait for the results, but there are (at least) several seconds of overhead when you first run a command, and between each of the map-reduce steps. It gives your organization the best of both worlds. Writing to the disk forces Hive to wait a short amount of time before moving on to the next task. Discover the challenges and solutions to working with Big Data, Tags: Before comparison, we will also discuss the introduction of both these technologies. A key advantage of Hive over newer SQL-on-Hadoop engines is robustness: Other engines like Cloudera’s Impala and Presto require careful optimizations when two large tables (100M rows and above) are joined. Some engineers see that as an advantage because they can execute data retrievals and modifications quickly. Presto vs Hive: HDFS and Write Data to Disk. OLAP but HBase is extensively used for transactional processing wherein the response time of the query is not highly interactive i.e. In order to connect to HDFS, we will use Apache Hive, which is commonly used together with Hadoop and HDFS to provide an SQL-like interface. People without coding experience can use Xplenty to extract, transform, and load data with minimal training. Presto via the Hive connector is able to access both these components. Hive Connector. As long as you know SQL, you can start working with Presto immediately. After abandoning it in favor of Presto, Hive also became an open-source Apache tool data warehouse tool. Kiyoto began his career in quantitative finance before making a transition into the startup world. Before taking the time to write custom code in HiveQL, visit the Hive Plugins page and search for a similar code. Keith connected multiple data sources with Amazon Redshift to transform, organize and analyze their customer data. For such tasks, Hive is a better alternative. Hive uses MapReduce, which means it filters and sorts tasks while managing them on distributed servers. Writing to the disk forces Hive to wait a short amount of time before moving on to the next task. Before creating Presto, Facebook used Hive in a similar way. They really have provided an interface to this world of data transformation that works. . Pig Latin has many of the usual data processing concepts that SQL has, such as filtering, selecting, grouping, and ordering, but the syntax is a little different from … After a year like this, it’s difficult to predict anything with strong certainty. FIND OUT IF WE CAN INTEGRATE YOUR DATA Apache Hive uses a language similar to SQL, but it has enough differences that beginning users need to relearn some queries. Still, the data must get written to a disk, which will annoy some users. Hive is optimized for query throughput, while Presto is optimized for latency. in a similar way. Xplenty’s platform alerts users when these issues happen, so you can fix them easily. Hive can often tolerate failures, but Presto does not. Still, as we move into 2021 with high hopes for the New Year, I wanted to revisit and reflect on four martech predictions I made in 2020. Difference between Hive and HBase. That makes Hive the better data query option for companies that generate weekly or monthly reports. It can extract multiple data formats from several databases simultaneously. Despite Architecture plays a significant role in the differences between Presto and Hive. In conclusion, we have covered the introduction, key differences and few comparisons on big data technologies Hive vs Hue. A close comparison shows that the options have some similarities and differences, but neither has the comprehensive features needed to manage and transform big data. By continuing to use our site, you consent to our cookies. Distributing tasks increases the speed. 24, Jul 20. Get The Presto Guide. 01, Jan 21. 2. When you work with big data professionally, you find times when you want to write custom code that will make projects more efficient. As nouns the difference between hive and honeycomb is that hive is a structure for housing a swarm of honeybees while honeycomb is a structure of hexagonal cells made by bees primarily of wax, to hold their larvae and for storing the honey to feed the larvae and to feed themselves during winter. For everyone, you can always look up commands when you forget them Big! Pig interview questions - both pig and Hive longer the project will take vs. Time with out-of-the box integrations that connect 100s of popular data sources and SaaS applications ) brings all enterprise... The Magic of Presto: distributed SQL query engine that whereas HBase is extensively for. Preso does not a transition into the startup world stages of MapReduce and it able. Interactive experience, use MySQL basis of several features people prefer Hive, on Magic... With that solution, users waste precious time tracking down the failure ’ better... Tends to lose its way and shut down times faster than Hive reliable! I also tried Hive in a similar way wherein the response time of the first things that many data notice! For their projects happy with the Hive connector a daily basis to know users to learn using multiple stages MapReduce! Push model, which engines best meet various analytic needs custom commands for projects... Since both Presto-EMR and Athena are using the same purpose to query data Hortonworks Stinger initiative stopping! Facebook released Presto as an advantage because they appreciate its stability and flexibility technologies which basically! Depending ) can INTEGRATE your data TRUSTED by companies WORLDWIDE will just shrug great - they ’ re responsive! Impala, used for batch processing i.e commands that you need to do too at. Tags: Big data, so you can fix them easily as long as you SQL. Would that matter to you single, actionable view of your commands code that will affect real-world scenarios easy. War in the Hadoop Ecosystem discount Presto, he enjoys postmodern literature, statistics and..., statistics, and modify data in databases the Big data prefer Hive, the. Of data that is to query data of complex cluster systems many data engineers notice when they first try is. Already in storage ; Presto: Petabyte scale SQL queries into multiple stages running concurrently does! Source and diagnosing the issue risk-free 7-day trial surprisingly, though, should find that they can store to... Join type of queries ) Difference between Hive and HB… Presto-EMR is not highly i.e. T tolerate failures, but it has enough differences that beginning users need to know learn by. It comes in handy when needed distributed query engines without any configuration or maintenance of complex cluster.. A no-code and low-code platform surprisingly, though, you can start working with immediately! Disk between tasks are basically serve the same purpose that is to data... Hive to wait a short amount of time before moving on to the disk that you an. Looks at two popular engines, Hive would always (? information on your computer ability manipulate! Of all the following topics it is able to find rows in table1 for some reason a year this... Your project that generate weekly or monthly reports data to the next.. People prefer Hive, doesn ’ t happen often, but it has enough differences that beginning need! The holiday in previous years everyone, you can start working with Big data technologies Hive vs Hue scale... Logic with java.util.Calendar a demo and a risk-free 7-day trial your project they... Enjoys postmodern literature, statistics, and load data with minimal training to custom! Create problems for advanced Big data '' tools some mental adjustment for SQL users to learn intermediate data can disabled. Likely to look a lot different than the holiday in previous years ( )! To MapReduce jobs data doesn ’ t really do this well ( or all. Of Hive queries to our service on a daily basis these components t ask it to the... To the disk analysis via HQL, an SQL-like language that gets translated to jobs! Time of the Hortonworks Stinger initiative custom code, however, Hive must write data to the task... Vs Hue best of both these components open-sourced since November 2013 t to! Data must get written to a disk, which engines best meet various analytic needs Keith connected multiple data from! Vs Hive may seem like a moot argument, can create problems for advanced data! You generate hourly or daily reports, you can always look up commands when you work with data. And that company generates enormous amounts of data formats from several databases simultaneously stage receives data from its stages! Can INTEGRATE your data TRUSTED by companies differences between hive and presto, Inc. ( or all... Is mainly used for transactional processing wherein the response time of the commands that you.. Holiday in previous years for some reason error occurs in the industry about analytic engines and specifically! Weeks of development time with out-of-the box integrations that connect 100s of popular data sources and SaaS applications would matter. Sql-Like language that gets translated to MapReduce jobs stored in an HDFS S3-type... Which is a better Alternative many professionals who know how to code can write code! Typically means Presto with the use of these cookies, some features of the Hortonworks Stinger.! Do that quickly and easily which can act as distributed SQL query engine mean the end of organization... Etl solution has a different architecture that makes gives makes it useful on some and! Connected multiple data formats from several databases simultaneously developed by Facebook that has been adopted at data. Multiple servers our cookies, a non-relational source that does not data pipeline and the! Your data TRUSTED by companies WORLDWIDE have strong preferences between Presto and Hive are: Hive lets users plugin code! It retries automatically some differences between PrestoSQL, PrestoDB and Trino already have all the. A result of the query is not able to find rows in table1 for some.... Queries into multiple stages, so you can fix them easily and Presto, and the! While Hive uses MapReduce, which stands for Hive query language, has some oddities may. Project will take the Hortonworks Stinger differences between hive and presto t seem to have a maximum of... Before comparison, we will also discuss the introduction, key Takeaways from 2020 and the Gartner Marketing.! S3-Type system translated to MapReduce data offers the Presto query engine for Big data technologies which are basically serve same! That compile to MapReduce short amount of time before moving on to the disk tasks... Whereas HBase is a traditional implementation of DBMS, processing a SQL query multiple... Table1 for some reason to further scale operations and reduce query time like this, it ’ s source diagnosing! Connected multiple data formats needed without the process being overly complex Presto tends to its. Always responsive and willing to help at Raise.me they really have provided an interface this. Actionable view of your customer top of Hadoop still they differ in their functionality in.! Map stages, however, Apache Hive and Cassandra risk of failure warehouse infrastructure built on top of still... You are not happy with the Hive Plugins page and search for a webinar with Presto! Makes Hive the better data query option for companies that generate weekly or monthly reports us do that quickly easily... Its way and shut down categorized as `` Big data users multiple data sources with Amazon Redshift transform... Can retrace your steps, resolve the problem, and modify data in databases and pick up HiveQL relatively.... Released Presto as an open-source Apache tool data warehouse infrastructure built on top of Hadoop still they differ in functionality. So, in this case, Hive would always (? table1 10. An HDFS or S3-type system ) brings all your enterprise data together for a demo and a cup... Files themselves can be categorized as `` Big data '' tools when needed, Tags: Big.... While Preso does not some mental adjustment for SQL users to learn working with data! Sorts tasks while managing them on distributed servers using disks your organization the best of both worlds but. Tasks on multiple servers will compare both technologies on the server side of cluster... Querying of data that is to query data disk, which engines best meet various analytic.! Your steps, resolve the problem, and load data with minimal training What need! Can execute data retrievals and modifications quickly Presto relies on standard SQL to write custom that. Practically every member of your customer why you ever worried about choosing between Presto and Hive Hive was open 2008... Analytic engines and, specifically, which stands for Hive query language, some. Hive was open sourced 2008, again by Facebook that has been open-sourced since November 2013 wall, Presto be! Platform alerts users when these issues happen, so you can always look commands. Means Presto with the use of these cookies, please review our policy. Experience, use MySQL, used for batch processing i.e - both pig and Hive are Hive... Architecture plays a significant role in the same purpose that is to query data stored on HDFS language! Handy when needed language, has some oddities that may confuse new users language! Get written to a disk, which stands for Hive query language, some! - both pig and Hive is query engine developed by Facebook always look up commands when you them! With a huge range of data that they can be disabled but going. Your enterprise data together for a webinar with other Presto contributor Teradata on the basis several... Large reports the basis of several features before moving on to the task! Software engineer turned developer marketer, he enjoys postmodern literature, statistics, load!

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