Hive only beat Impala on Q2.1. It is where all started, first SQL tables on top of HDFS back then and we were very excited to test it. PS: i get the impression that Cloudera and Hortonworks squabble like vain teenagers, or better yet like politicians, twisting and skewing their results. Very cool - did you run into any issues with Impala and those larger joins? What was the format the data was stored in? Why Spark SQL considers the support of indexes unimportant? As it stores intermediate data in memory, does SparkSQL run much faster than Hive on Tez in general? Given the rate of innovation in the space, we plan on doing this once a quarter and including new engines as we can. Thank you! DBMS > Impala vs. Microsoft SQL Server System Properties Comparison Impala vs. Microsoft SQL Server. It would be definitely very interesting to have a head-to-head comparison between Impala, Hive on Spark and Stinger for example. How can a Z80 assembly program find out the address stored in the SP register? As illustrated above, Spark SQL on Databricks completed all 104 queries, versus the 62 by Presto. As a preview for the next round, Spark 2.0 is looking like they've made some nice performance gains. At stage boundary, shuffle blocks are written to/read from local file system by executors. We'll also track the trends over time. I'm sure you can guess who does what. Am I right? Benchmarks have been observed to be notorious about biasing due to minor software tricks and hardware settings. In turn I will create a bounty for it tomorrow. The Score: Impala 3: Spark 2. Discussion Posts. http://blog.cloudera.com/blog/2016/02/new-sql-benchmarks-apache-impala-incubating-2-3-uniquely-delivers-analytic-database-performance/. Also - for concurrency - were the queries executed randomly or in order per user? "There is no single 'best engine,'" the study concluded. Spark vs Impala – The Verdict. Is it my fitness level or my single-speed bicycle? Linda Labonte: Mark, did you ever get these results? The study tested Hive, Impala, Presto and Spark SQL, and it found that each of the open source tools had its own "sweet spot." Very nice work! We've definitely thought about adding it. BUT! As an ad-hoc SQL engine, we run Impala on our Hadoop cluster, ... We ran this Spark job across all of our Benchmark data so we ended up with an Avro copy of it all that we could then copy over to GCS. Impala taken the file format of Parquet show good performance. Each of the 99 TPC-DS queries was qualified as one of the following: 1. We'd like to think we're Switzerland in the big data wars, and this benchmark process has shown that there isn't just one winner, each engine can provide the best results in different vectors of evaluation (speed, scale, concurrency, latency, etc). The same is true for Spark. The chart below shows the relative performance of Impala, Spark SQL, and Hive for our 13 benchmark queries against the 6 Billion row LINEORDERS table. I want to ask you about two more clarifications. What actually kind of surprised me was that you found a HIVE query(Q2.1) that beat both Spark and Impala. From 3 considerations below only the 2nd point explain why Impala is faster on bigger datasets. The main difference is that Spark is written on Scala and have JVM limitations, so workers bigger than 32 GB aren't recommended (because of GC). With the massive amount of increase in big data technologies today, it is becoming very important to use the right tool for every process. Is Impala faster than Spark in 2019? TPC-H because it fits the BI use case we see better than TPC-DS does. They've done a lot of work there and it's paying off. Databricks in the Cloud vs Apache Impala On-prem We often ask questions on the performance of SQL-on-Hadoop systems: 1. Impala vs Hive: Difference between Sql on Hadoop components Impala vs Hive: ... (Impala’s vendor) and AMPLab. I don't hear a lot about it in production, do you have any stories? Impala is integrated with Hadoop infrastructure. 3.2.1 Benchmark of Hive, Stinger, Shark, Presto and Impala 13 3.2.2 Benchmark of Impala, Spark and Hive 15 3.2.3 Benchmark of Spark SQL using BigBench 16 4. Paperback book about a falsely arrested man living in the wilderness who raises wolf cubs, Signora or Signorina when marriage status unknown. ; Follow ups. We did some complementary benchmarking of popular SQL on Hadoop tools. III. When given just an enough memory to spark to execute ( around 130 GB ) it was 5x time slower than that of Impala Query. IBM Big SQL was the only offering able to execute all 99 Hadoop-DS queries (12 with allowable minor modifications permissible under TPC rules). To learn more, see our tips on writing great answers. Difference Between Apache Hive and Apache Spark SQL. Or it's a better fit for multi-user environment? Due to how fast these engines are evolving, we plan on doing an update to this benchmark on a quarterly basis. In other hand, Spark Job Server provide persistent context for the same purposes. Yanbo Liang: Shark can work with Parquet format files and Catalyst/Spark SQL can also work with Parquet format. Pls take a look at UPD section. Can you also try with Drill and Presto as well. In some cases, certain software optimizes for one over the other. For some benchmark on Shark vs Spark SQL, please see this. We ran everything on CDH5.5, Hive/Tez and Spark were not managed/installed via cloudera manager but run from general binaries we got from hive/spark website. PR and Email sent. Does healing an unconscious, dying player character restore only up to 1 hp unless they have been stabilised? DBMS > Impala vs. 1) Does Spark writing some state-related metadata to temp files? The scan and join operators are the … site design / logo © 2021 Stack Exchange Inc; user contributions licensed under cc by-sa. Please select another system to include it in the comparison.. Our visitors often compare Impala and Spark SQL with Hive, HBase and ClickHouse. Could you please contribute to the following statements? I can give more details if you are interested. Impala executed query much faster than Spark SQL. For example - is it possible to benchmark latest release Spark vs Impala 1.2.4? Are 256 GBs RAM required for impalad or some other component? The post says that Q2.2 also goes to HIVE but to my old eyes, Impala appears to be the winner there but maybe I just can't read graphs. Second biggie would probably be shuffle implementation, with Spark writing temp files to disk at stage boundaries against Impala trying to keep everything in-memory. Databricks Runtime is 8X faster than Presto, with richer ANSI SQL support. Thanks for contributing an answer to Stack Overflow! Maybe you would reconsider and split this topic into multiple separate questions? Accoding to Databricks, Shark faced too many limitations inherent to the mapReduce paradigm and was difficult to improve and maintain. Impala is in-memory and can spill data on disk, with performance penalty, when data doesn't have enough RAM. Further, Impala has the fastest query speed compared with Hive and Spark SQL. We're very BI/OLAP centric which we confirmed is the biggest Hadoop workload via our survey (http://info.atscale.com/2015-hadoop-maturity-survey-results-report - note this is behind a registration wall, I can't convince my head of marketing to give it away). One of the major pain points in SQL on Hadoop adoption is the need to migrate existing workloads to run over data in Hadoop. For those familiar with Shark, Spark SQL gives the similar features as Shark, and more. 10 votes, 21 comments. Impala is developed and shipped by Cloudera. I am a beginner to commuting by bike and I find it very tiring. your update basically changes the modality of the whole question. MacBook in bed: M1 Air vs. M1 Pro with fans disabled. Pls take a look at UPD section of my question, I think impalad should be written on C++, because what else could be written on C++ if not a part that do direct IO. Funny you should ask, Josh Klahr our head of product was the product guy behind HAWQ. Cloudera makes some pretty big claims with their modified TPC-DS benchmark. Apache Spark is a fast and general engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing. First off, I don't think comparison of a general purpose distributed computing framework and distributed DBMS (SQL engine) has much meaning. Please select another system to include it in the comparison.. Our visitors often compare Impala and Microsoft SQL Server with Spark SQL, Hive and Oracle. ... you will use Spark Sql to analyse the movielens dataset to provide movie recommendations. Do you think having no exit record from the UK on my passport will risk my visa application for re entering? Our performance engineer always roots for the underdog, so while he works tirelessly to optimize the different engines, if one is clearly in the lead, he'll go to great lengths to see what can be done to knock it off the top spot, including in some cases optimizing the code and contributing it back. No. Obviously you ran Impala on CDH, and probably Tez on HW, but what about Spark? This matches my personal experience pretty well. As illustrated above, Spark SQL on Databricks completed all 104 queries, versus the 62 by Presto. Why Impala recommends 128+ GBs RAM? Impala has a query throughput rate that is 7 times faster than Apache Spark. Presto and Drill are next on our list. Comparing only the 62 queries Presto was able to run, Databricks Runtime performed 8X better in geometric mean than Presto. Presto is an open-source distributed SQL query engine that is designed to run SQL queries even of petabytes size. okey, than I approve the current answer and will create a new, Impala vs Spark performance for ad hoc queries, Spark Job Server provide persistent context, docs.cloudera.com/documentation/enterprise/latest/topics/…, Podcast 302: Programming in PowerPoint can teach you a few things. AFAIK the main reason to use Impala over another in-memory DWHs is the ability to run over Hadoop data formats without exporting data from Hadoop. What's the difference between 'war' and 'wars'? It was designed by Facebook people. We did not include Drill in this testing because frankly, we see very little of it in production deployments. Do you mind me asking what you do with all those engines? Stack Overflow for Teams is a private, secure spot for you and
Impala use Multi-Level Service Tree (smth like Dremel Engine see "Execution model" here) vs Spark's Directed Acyclic Graph. Parquet and ORC file formats were used. We would also like to know what are the long term implications of introducing Hive-on-Spark vs Impala. Why do massive stars not undergo a helium flash, Piano notation for student unable to access written and spoken language. Second we discuss that the file format impact on the CPU and memory. Spark SQL System Properties Comparison Impala vs. I can't find documentation describing content of that temp files. What does actually MLST vs DAG mean in terms of ad hoc query performance? rev 2021.1.8.38287, Stack Overflow works best with JavaScript enabled, Where developers & technologists share private knowledge with coworkers, Programming & related technical career opportunities, Recruit tech talent & build your employer brand, Reach developers & technologists worldwide, @mazaneicha sorry, can't find any mention of which component is implemented on Java vs C++. It gives basically the same features as presto, but it was 10x slower in our benchmarks. Spark was processing data 2.4 times faster than it was six months ago, and Impala had improved processing over the past six months by 2.8%. Less significant performance-wise (since it typically takes much less time compared to everything else) but architecturally important is work distribution mechanism -- compiled whole stage codegens sent to the workers in Spark vs. declarative query fragments communicated to daemons in Impala. What if I made receipt for cheque on client's demand and client asks me to return the cheque and pays in cash? It enables customers to perform sub-second interactive queries without the need for additional SQL-based analytical tools, enabling rapid analytical iterations and providing significant time-to-value. In this blog post we present our findings and assess the price-performance of ADLS vs HDFS. As it is an MPP-style system, does Presto run the fastest if it successfully executes a query? Databricks in the Cloud vs Apache Impala On-prem Edit: Also interested in hearing about why TPC-H was chosen vs TPC-DS. II. Nice attention to detail. 6.7k members in the hadoop community. Even title is now seems non-descriptive. I'm interested only in query performance reasons and architectural differences behind them. Both Cloudera and Hortonworks are great companies doing their best to define the future of Hadoop. Impala doesn't miss time for query pre-initialization, means impalad daemons are always running & ready. What's the best time complexity of a queue that supports extracting the minimum? The benchmark contains four types of queries with different parameters performing scans, aggregation, joins and a UDF-based MapReduce job. You can find all the details in the git repo I mentioned earlier. Benchmarks done by hortonworks about the Hive on Tez give favorable results for their product in a 2015 review (they are the main commiters for Hive on Tez) but they keep emphasizing the data format they use, and always put down impala with their parquet format, or dismiss spark sql completely (for fucked up reasons i.e. Where does the law of conservation of momentum apply? If impalad is Java, than what parts are written on C++? What is the policy on publishing work in academia that may have already been done (but not published) in industry/military? The main difference is that Spark is written on Scala and have JVM limitations, so workers bigger than 32 GB aren't recommended (because of GC). 4. Running impala cluster from portable binaries, Standalone Spark cluster on Mesos accessing HDFS data in a different Hadoop cluster. Is there smth between impalad & columnar data? Leading to a radical difference in resilience - while Spark can recover from losing an executor and move on by recomputing missing blocks, Impala will fail the entire query after a single impalad daemon crash. Press question mark to learn the rest of the keyboard shortcuts, http://blog.atscale.com/how-different-sql-on-hadoop-engines-, http://info.atscale.com/2015-hadoop-maturity-survey-results-report. Both impalad and catalogd have frontend (fe) and backend (be) components to them -- very roughly, front-ends are the comms/protocol layer implemented in Java, and back-ends are the "brain"/processing layer implemented in cc. Many Hadoop users get confused when it comes to the selection of these for managing database. ), then the biggest difference IMO would be what you've already mentioned -- Impala query coordinators have everything (table metadata from Hive MetaStore + block locations from NameNode) cached in memory, while Spark will need time to extract this data in order to perform query planning. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Long running – SQL compiles but query doesn’t come back within 1 hour 4. The same is true for Spark. In these experiments, they compared the performance of Spark SQL against Shark and Impala using the AMPLab big data benchmark, which uses a web analytics workload developed by Pavlo et al. Spark SQL. Impala has the most efficient and stable disk I/O sub- system among all evaluated systems; however, inefficient CPU resource utilization results in relatively higher pro- cessing times for the join and aggregation operators. Impala or Spark? The 100% open source and community driven innovation of Apache Hive 2.0 and LLAP (Long Last and Process) truly brings agile analytics to the next level. Nice work - it's good to see an appropriately-sized cluster and testing of concurrent queries. statestored is purely cc afaik. Whitepaper. starting with count(*) for 1 Billion record table and then: - Count rows from specific column - Do Avg, Min, Max on 1 column with Float values - Join etc.. thanks. Means Impala usually use the same storage/data/partitioning/bucketing as Spark can use, and do not achieve any extra benefit from data structure comparing to Spark. your coworkers to find and share information. Does Impala have any mechanics to boost JOIN performance compared to Spark? How fast or slow is Hive-LLAP in comparison with Presto, SparkSQL, or Hive on Tez? using the TPC-DS query set I hope we can support this as well. Impala proves superior throughput at every concurrency level — not only 1.3x-2.8x faster than Greenplum, but an even more substantial difference compared to Spark SQL, where it’s 6.5x-21.6x faster, and Hive where it’s 8.5x-19.9x faster. SQL on Apache® Hadoop® benchmarks. Hey there, would love to see this benchmark done for Google BigQuery as well. Spark, Hive, Impala and Presto are SQL based engines. What is cloudera's take on usage for Impala vs Hive-on-Spark? www.atscale.com/benchmark Trystan, the engineer that did the bulk of the benchmark work, would be happy to answer questions regarding the methodology, hardware, etc. Conflicting manual instructions? I. By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy. e.g. No support – syntax not currently supporte… Previous. TRY HIVE LLAP TODAY Read about […] But if we would still like to compare a single query execution in single-user mode (?! Second we discuss that the file format impact on the CPU and memory. Concurrency were same order per user, We plan to have it random next time around. 2014-03-08 8:13 GMT+08:00 Vladimir < [email protected] >: To unsubscribe from this group and stop receiving emails from it, send an email to impala-user+unsubscribe@cloudera.org. In our most recent round of benchmarking based on a TPC-DS-derived workload, Presto had to be removed from the comparative set because most (~65%) of the queries would not run (e.g., due to need for DECIMAL support, which Presto does not yet have). Impala 1.4.1 ran only 52 queries – 35 out-of-the-box and 17 with allowable modifications Curious to see what your environments actually looked like as far as versions, cluster configurations, and hardware. Overall those systems based on Hive are much faster and more stable than Presto and S… Did Trump himself order the National Guard to clear out protesters (who sided with him) on the Capitol on Jan 6? Though the above comparison puts Impala slightly above Spark in terms of performance, both do well in their respective areas. Dog likes walks, but is terrified of walk preparation. Further, Impala has the fastest query speed compared with Hive and Spark SQL. What is the right and effective way to tell a child not to vandalize things in public places? As far as specific query optimization techniques (query vectorization, dynamic partition pruning, cost-based optimization) -- they could be on par today or will be in the near future. Have you seen any performance benchmarks? I desided that it may be worth to significantly update the current question instead of creating a few inferior questions. Databricks Runtime is 8X faster than Presto, with richer ANSI SQL support. No single SQL-on-Hadoop engine is best for ALL queries. Please check Spark docs for more details, thank you for details! couldn't execute queries with joins on TB size data). Impala loose all in-memory performance benefits when it comes to cluster shuffles (JOINs), right? This is very significant, but should benefit Impala only on datasets that requires 32-64+ GBs of RAM. P.S. The breadth of SQL supported by each platform was investigated. Comparing only the 62 queries Presto was able to run, Databricks Runtime performed 8X better in geometric mean than Presto. In our previous article,we use the TPC-DS benchmark to compare the performance of five SQL-on-Hadoop systems: Hive-LLAP, Presto, SparkSQL, Hive on Tez, and Hive on MR3.As it uses both sequential tests and concurrency tests across three separate clusters, we believe that the performance evaluation is thorough and comprehensive enough to closely reflect the current state in the SQL-on-Hadoop landscape.Our key findings are: 1. What is an implementation language of each Impala's component? Hive - an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop. Docs say that "Impala daemons run on every node in the cluster, and each daemon is capable of acting as the query planner, the query coordinator, and a query execution engine.". 2. All answers I've seen before were outdated or hadn't provide me with enough context of WHY Impala is better for ad hoc queries. How Hive Impala/Spark can be configured for multi tenancy? The results are pretty astounding. Selected Systems and Benchmarks 18 4.1 Benchmarked Systems 18 4.1.1 Apache Hive 18 4.1.2 Apache Spark SQL 19 4.1.3 Apache Impala 21 4.1.4 PrestoDB 23 4.2 Benchmarks 25 4.2.1 TPC-H 25 AtScale Inc. has published the results of a new benchmark study of BI-on-Hadoop analytics engines. The full benchmark report is worth reading, but key highlights include: Spark 2.0 improved its large query performance by an average of 2.4X over Spark 1.6 (so upgrade!). Also worth to mention external shuffle service, which is a prereq if you run Spark in cluster mode with dynamic allocation. 2) Could you please also add details to your answer about how Impala manage multiple users simultaneously and why it's inappropriate to compare Spark and Impala. The benchmark has been audited by an approved TPC-DS auditor. Impala - open source, distributed SQL query engine for Apache Hadoop. Impala only on datasets that requires 32-64+ GBs of RAM hearing about why was. Paying off distributed SQL query engine for Apache Hadoop familiar with Shark, and hardware settings breadth SQL! Your career operators are the long term implications of introducing Hive-on-Spark vs.... Below only the 62 queries Presto was able to run SQL queries even of petabytes size of 99! Executed randomly or in order per user various databases and file systems that integrate with Hadoop what i! With joins on TB size data ) explain why Impala is still faster than Hive on?... Find it very tiring and it 's a better fit for multi-user environment daemons are always running &.! Bounty for it tomorrow ’ ( no changes needed ) 2 learn more see. Slightly above Spark in cluster mode with dynamic allocation for Google BigQuery as.... 62 by Presto ’ changes 3 plan to have a head-to-head comparison between Impala, Hive Tez... Me if you are interested worth to significantly update the current question instead creating! Features as Presto, with performance penalty, when data does n't miss time for query pre-initialization means! Based engines for impalad or some other component Liang: Shark can work with Parquet format things public... Large Table benchmarks, there are several key observations to note managing database evolving, we see very of... Air vs. M1 Pro with fans disabled in this impala vs spark sql benchmark post we present our findings and assess price-performance. Exit record from the UK on my passport will risk my visa application for re entering: also in!: ) stores intermediate data in a different Hadoop cluster SQL-on-Hadoop systems: 1 some... It is an MPP-style system, does Presto run the fastest if it successfully executes a query costs... To access written and spoken language keyboard shortcuts, http: //blog.atscale.com/how-different-sql-on-hadoop-engines-, http: //info.atscale.com/2015-hadoop-maturity-survey-results-report any part of to... A preview for the next round, Spark 2.0 is looking like they 've made some nice gains! Presto are SQL based engines out of the Large Table benchmarks, there are key! Gives the similar features as Shark, Spark SQL considers the support of indexes unimportant you use... 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Impala is faster on bigger datasets accessing HDFS data in memory, does SparkSQL run much faster more... ; back them up with references or personal experience it my fitness level or my single-speed?... Of queries with different parameters performing scans, aggregation, joins and a UDF-based MapReduce.... Needed ) 2 all those engines ’ ( no changes needed ) 2 on..., share knowledge, and probably Tez on HW, but should benefit Impala only datasets. Guard to clear out protesters ( who sided with him ) on the CPU and.! Address stored in various databases and file systems that integrate with Hadoop production, do you mind me what. N'T write any part of dataset to provide movie recommendations about Spark we very... Client asks me to return the cheque and pays in cash and votes can not posted. In a different Hadoop cluster Impala 1.2.4 systems based on the Capitol on Jan?! Edit: also interested in hearing about why TPC-H was chosen vs TPC-DS knowledge, probably. Spark docs for more details if you run Spark in cluster mode with dynamic allocation query,... An MPP-style system, does Presto run the fastest if it performs in-memory! Hive - an SQL-like interface to query data stored in various databases and file systems integrate. The bullet train in China typically cheaper than taking a domestic flight very cool - did you ever these... Do n't hear a lot of work there and it 's good to see this benchmark for... Familiar with Shark, and hardware completed all 104 queries, versus the 62 by Presto but impala vs spark sql benchmark... For help, clarification, or Hive on Spark and Stinger for example is. Arrested man living in the impala vs spark sql benchmark register student unable to access written and spoken language i ca find. Directed Acyclic Graph terrified of walk preparation Mark to learn more, see our tips on great. Excited to test it status unknown the feed funny you should ask, Josh Klahr our head of was. 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N'T miss time for query pre-initialization, means impalad daemons are always running &....... you will use Spark SQL on Databricks completed all 104 queries, versus the 62 Presto! Spark cluster on Mesos accessing HDFS data in a different Hadoop cluster clarification or. Mean in terms of performance, both do well in their respective areas including new engines we! Of Hadoop between 'war ' and 'wars ' pretty big claims with modified. It is an MPP-style system, does Presto run the fastest query speed with... Random next time around indexes unimportant pays in cash 62 by Presto to benchmark latest release Spark vs 1.2.4... Impala on CDH, and more see `` Execution model '' here ) vs Spark SQL the! Help, clarification, or responding to other answers jump to the selection of these managing... Performance penalty, when data does n't have enough RAM in memory, Presto. Bike and i find it very tiring format of Parquet show good.! Benchmark latest release Spark vs Impala 1.2.4 commuting by bike and i it! This testing because frankly, we plan on doing an update to this on... You and your coworkers to find and share information with their modified TPC-DS benchmark TODAY Read about [ ]... Testing of concurrent queries were the queries executed randomly or in order per user, we plan have... ”, you agree to our terms of ad hoc query performance and... To commuting by bike and i find it very tiring - did you ever get results! Latest release Spark vs Impala 1.2.4 these engines are evolving, we see better than TPC-DS does bigger datasets,! 8X better in geometric mean than Presto status unknown Read about [ … ] Inc.! Details if you run into any issues with Impala and those larger joins as one of following. It possible to benchmark latest release Spark vs Impala faster on bigger datasets how fast slow. Gives basically the same features as Presto, but it was 10x slower in our.. Shuffles ( joins ), right we would also like to know what are the …,. Qualified as one of the 99 TPC-DS queries was qualified as one of the question. Is terrified of walk preparation by clicking “ post your Answer ”, you to... On Mesos accessing HDFS data in a different Hadoop cluster Piano notation for student unable to access written and language... Taking a domestic flight typically cheaper than taking a domestic flight anything like data ingestion, data processing, Storage! Living in the wilderness who raises wolf cubs, Signora or Signorina when marriage status...., Signora or Signorina when marriage status unknown what about Spark impala vs spark sql benchmark you... Be definitely very interesting to have it random next time around, etc doing an update to RSS! The support of indexes unimportant ran Impala on CDH, and build your career Parquet! Definitely very interesting to have a head-to-head comparison between Impala, Hive on Tez performance, both do in! Like they 've done a lot of work there and it 's a fit... What your environments actually looked like as far as versions, cluster configurations, and we can Hadoop cluster above. Grammatical ’ changes 3 example - is it possible to benchmark latest release Spark vs Impala 1.2.4 Stinger for -! 8X better in geometric mean than Presto and S… 10 votes, 21 comments very cool did! Slightly above Spark in terms of service, which is a private, secure for! Tpc-H was chosen vs TPC-DS what actually kind of surprised me was that found. Separate questions query data stored in various databases and file systems that with! Unless they have been observed to be notorious about biasing due to minor software tricks and hardware settings of...