+1 Sent from my iPhone
> On Jan 13, 2019, at 5:34 PM, Thomas Weise <t...@apache.org> wrote: > > Hi all, > > Following the discussion of the Hudi proposal in [1], this is a vote > on accepting Hudi into the Apache Incubator, > per the ASF policy [2] and voting rules [3]. > > A vote for accepting a new Apache Incubator podling is a > majority vote. Everyone is welcome to vote, only > Incubator PMC member votes are binding. > > This vote will run for at least 72 hours. Please VOTE as > follows: > > [ ] +1 Accept Hudi into the Apache Incubator > [ ] +0 Abstain > [ ] -1 Do not accept Hudi into the Apache Incubator because ... > > The proposal is included below, but you can also access it on > the wiki [4]. > > Thanks for reviewing and voting, > Thomas > > [1] > https://lists.apache.org/thread.html/12e2bdaa095d68dae6f8731e473d3d43885783177d1b7e3ff2f65b6d@%3Cgeneral.incubator.apache.org%3E > > [2] > https://incubator.apache.org/policy/incubation.html#approval_of_proposal_by_sponsor > > [3] http://www.apache.org/foundation/voting.html > > [4] https://wiki.apache.org/incubator/HudiProposal > > > > = Hudi Proposal = > > == Abstract == > > Hudi is a big-data storage library, that provides atomic upserts and > incremental data streams. > > Hudi manages data stored in Apache Hadoop and other API compatible > distributed file systems/cloud stores. > > == Proposal == > > Hudi provides the ability to atomically upsert datasets with new values in > near-real time, making data available quickly to existing query engines > like Apache Hive, Apache Spark, & Presto. Additionally, Hudi provides a > sequence of changes to a dataset from a given point-in-time to enable > incremental data pipelines that yield greater efficiency & latency than > their typical batch counterparts. By carefully managing number of files & > sizes, Hudi greatly aids both query engines (e.g: always providing > well-sized files) and underlying storage (e.g: HDFS NameNode memory > consumption). > > Hudi is largely implemented as an Apache Spark library that reads/writes > data from/to Hadoop compatible filesystem. SQL queries on Hudi datasets are > supported via specialized Apache Hadoop input formats, that understand > Hudi’s storage layout. Currently, Hudi manages datasets using a combination > of Apache Parquet & Apache Avro file/serialization formats. > > == Background == > > Apache Hadoop distributed filesystem (HDFS) & other compatible cloud > storage systems (e.g: Amazon S3, Google Cloud, Microsoft Azure) serve as > longer term analytical storage for thousands of organizations. Typical > analytical datasets are built by reading data from a source (e.g: upstream > databases, messaging buses, or other datasets), transforming the data, > writing results back to storage, & making it available for analytical > queries--all of this typically accomplished in batch jobs which operate in > a bulk fashion on partitions of datasets. Such a style of processing > typically incurs large delays in making data available to queries as well > as lot of complexity in carefully partitioning datasets to guarantee > latency SLAs. > > The need for fresher/faster analytics has increased enormously in the past > few years, as evidenced by the popularity of Stream processing systems like > Apache Spark, Apache Flink, and messaging systems like Apache Kafka. By > using updateable state store to incrementally compute & instantly reflect > new results to queries and using a “tailable” messaging bus to publish > these results to other downstream jobs, such systems employ a different > approach to building analytical dataset. Even though this approach yields > low latency, the amount of data managed in such real-time data-marts is > typically limited in comparison to the aforementioned longer term storage > options. As a result, the overall data architecture has become more complex > with more moving parts and specialized systems, leading to duplication of > data and a strain on usability. > > Hudi takes a hybrid approach. Instead of moving vast amounts of batch data > to streaming systems, we simply add the streaming primitives (upserts & > incremental consumption) onto existing batch processing technologies. We > believe that by adding some missing blocks to an existing Hadoop stack, we > are able to a provide similar capabilities right on top of Hadoop at a > reduced cost and with an increased efficiency, greatly simplifying the > overall architecture in the process. > > Hudi was originally developed at Uber (original name “Hoodie”) to address > such broad inefficiencies in ingest & ETL & ML pipelines across Uber’s data > ecosystem that required the upsert & incremental consumption primitives > supported by Hudi. > > == Rationale == > > We truly believe the capabilities supported by Hudi would be increasingly > useful for big-data ecosystems, as data volumes & need for faster data > continue to increase. A detailed description of target use-cases can be > found at https://uber.github.io/hudi/use_cases.html. > > Given our reliance on so many great Apache projects, we believe that the > Apache way of open source community driven development will enable us to > evolve Hudi in collaboration with a diverse set of contributors who can > bring new ideas into the project. > > == Initial Goals == > > * Move the existing codebase, website, documentation, and mailing lists to > an Apache-hosted infrastructure. > * Integrate with the Apache development process. > * Ensure all dependencies are compliant with Apache License version 2.0. > * Incrementally develop and release per Apache guidelines. > > == Current Status == > > Hudi is a stable project used in production at Uber since 2016 and was open > sourced under the Apache License, Version 2.0 in 2017. At Uber, Hudi > manages 4000+ tables holding several petabytes, bringing our Hadoop > warehouse from several hours of data delays to under 30 minutes, over the > past two years. The source code is currently hosted at github.com ( > https://github.com/uber/hudi ), which will seed the Apache git repository. > > === Meritocracy === > > We are fully committed to open, transparent, & meritocratic interactions > with our community. In fact, one of the primary motivations for us to enter > the incubation process is to be able to rely on Apache best practices that > can ensure meritocracy. This will eventually help incorporate the best > ideas back into the project & enable contributors to continue investing > their time in the project. Current guidelines ( > https://uber.github.io/hudi/community.html#becoming-a-committer) have > already put in place a meritocratic process which we will replace with > Apache guidelines during incubation. > > === Community === > > Hudi community is fairly young, since the project was open sourced only in > early 2017. Currently, Hudi has committers from Uber & Snowflake. We have a > vibrant set of contributors (~46 members in our slack channel) including > Shopify, DoubleVerify and Vungle & others, who have either submitted > patches or filed issues with hudi pipelines either in early production or > testing stages. Our primary goal during the incubation would be to grow the > community and groom our existing active contributors into committers. > > === Core Developers === > > Current core developers work at Uber & Snowflake. We are confident that > incubation will help us grow a diverse community in a open & collaborative > way. > > === Alignment === > > Hudi is designed as a general purpose analytical storage abstraction that > integrates with multiple Apache projects: Apache Spark, Apache Hive, Apache > Hadoop. It was built using multiple Apache projects, including Apache > Parquet and Apache Avro, that support near-real time analytics right on top > of existing Apache Hadoop data lakes. Our sincere hope is that being a part > of the Apache foundation would enable us to drive the future of the project > in alignment with the other Apache projects for the benefit of thousands of > organizations that already leverage these projects. > > == Known Risks == > > === Orphaned products === > > The risk of abandonment of Hudi is low. It is used in production at Uber > for petabytes of data and other companies (mentioned in community section) > are either evaluating or in the early stage for production use. Uber is > committed to further development of the project and invest resources > towards the Apache processes & building the community, during incubation > period. > > === Inexperience with Open Source === > > Even though the initial committers are new to the Apache world, some have > considerable open source experience - Vinoth Chandar (Linkedin voldemort, > Chromium), Prasanna Rajaperumal (Cloudera experience), Zeeshan Qureshi > (Chromium) & Balaji Varadarajan (Linkedin Databus). We have been > successfully managing the current open source community answering questions > and taking feedback already. Moreover, we hope to obtain guidance and > mentorship from current ASF members to help us succeed with the incubation. > > === Length of Incubation === > > We expect the project be in incubation for 2 years or less. > > === Homogenous Developers === > > Currently, the lead developers for Hudi are from Uber. However, we have an > active set of early contributors/collaborators from Shopify, DoubleVerify > and Vungle, that we hope will increase the diversity going forward. Once > again, a primary motivation for incubation is to facilitate this in the > Apache way. > > === Reliance on Salaried Developers === > > Both the current committers & early contributors have several years of core > expertise around data systems. Current committers are very passionate about > the project and have already invested hundreds of hours towards helping & > building the community. Thus, even with employer changes, we expect they > will be able to actively engage in the project either because they will be > working in similar areas even with newer employers or out of belief in the > project. > > === Relationships with Other Apache Products === > > To the best of our knowledge, there are no direct competing projects with > Hudi that offer all of the feature set namely - upserts, incremental > streams, efficient storage/file management, snapshot isolation/rollbacks - > in a coherent way. However, some projects share common goals and technical > elements and we will highlight them here. Hive ACID/Kudu both offer upsert > capabilities without storage management/incremental streams. The recent > Iceberg project offers similar snapshot isolation/rollbacks, but not > upserts or other data plane features. A detailed comparison with their > trade-offs can be found at https://uber.github.io/hudi/comparison.html. > > We are committed to open collaboration with such Apache projects and > incorporate changes to Hudi or contribute patches to other projects, with > the goal of making it easier for the community at large, to adopt these > open source technologies. > > === Excessive Fascination with the Apache Brand === > > This proposal is not for the purpose of generating publicity. We have > already been doing talks/meetups independently that have helped us build > our community. We are drawn towards Apache as a potential way of ensuring > that our open source community management is successful early on so hudi > can evolve into a broadly accepted--and used--method of managing data on > Hadoop. > > == Documentation == > [1] Detailed documentation can be found at https://uber.github.io/hudi/ > > == Initial Source == > > The codebase is currently hosted on Github: https://github.com/uber/hudi . > During incubation, the codebase will be migrated to an Apache > infrastructure. The source code already has an Apache 2.0 licensed. > > == Source and Intellectual Property Submission Plan == > > Current code is Apache 2.0 licensed and the copyright is assigned to Uber. > If the project enters incubator, Uber will transfer the source code & > trademark ownership to ASF via a Software Grant Agreement > > == External Dependencies == > > Non apache dependencies are listed below > > * JCommander (1.48) Apache-2.0 > * Kryo (4.0.0) BSD-2-Clause > * Kryo (2.21) BSD-3-Clause > * Jackson-annotations (2.6.4) Apache-2.0 > * Jackson-annotations (2.6.5) Apache-2.0 > * jackson-databind (2.6.4) Apache-2.0 > * jackson-databind (2.6.5) Apache-2.0 > * Jackson datatype: Guava (2.9.4) Apache-2.0 > * docker-java (3.1.0-rc-3) Apache-2.0 > * Guava: Google Core Libraries for Java (20.0) Apache-2.0 > * bijection-avro (0.9.2) Apache-2.0 > * com.twitter.common:objectsize (0.0.12) Apache-2.0 > * Ascii Table (0.2.5) Apache-2.0 > * config (3.0.0) Apache-2.0 > * utils (3.0.0) Apache-2.0 > * kafka-avro-serializer (3.0.0) Apache-2.0 > * kafka-schema-registry-client (3.0.0) Apache-2.0 > * Metrics Core (3.1.1) Apache-2.0 > * Graphite Integration for Metrics (3.1.1) Apache-2.0 > * Joda-Time (2.9.6) Apache-2.0 > * JUnit CPL-1.0 > * Awaitility (3.1.2) Apache-2.0 > * jersey-connectors-apache (2.17) GPL-2.0-only CDDL-1.0 > * jersey-container-servlet-core (2.17) GPL-2.0-only CDDL-1.0 > * jersey-core-server (2.17) GPL-2.0-only CDDL-1.0 > * htrace-core (3.0.4) Apache-2.0 > * Mockito (1.10.19) MIT > * scalatest (3.0.1) Apache-2.0 > * Spring Shell (1.2.0.RELEASE) Apache-2.0 > > All of them are Apache compatible > > == Cryptography == > > No cryptographic libraries used > > == Required Resources == > > === Mailing lists === > > * priv...@hudi.incubator.apache.org (with moderated subscriptions) > * d...@hudi.incubator.apache.org > * comm...@hudi.incubator.apache.org > * u...@hudi.incubator.apache.org > > === Git Repositories === > > Git is the preferred source control system: git:// > git.apache.org/incubator-hudi > > === Issue Tracking === > > We prefer to use the Apache gitbox integration to sync Github & Apache > infrastructure, and rely on Github issues & pull requests for community > engagement. If this is not possible, then we prefer JIRA: Hudi (HUDI) > > == Initial Committers == > > * Vinoth Chandar (vinoth at uber dot com) (Uber) > * Nishith Agarwal (nagarwal at uber dot com) (Uber) > * Balaji Varadarajan (varadarb at uber dot com) (Uber) > * Prasanna Rajaperumal (prasanna dot raj at gmail dot com) (Snowflake) > * Zeeshan Qureshi (zeeshan dot qureshi at shopify dot com) (Shopify) > * Anbu Cheeralan (alunarbeach at gmail dot com) (DoubleVerify) > > == Sponsors == > > === Champion === > Julien Le Dem (julien at apache dot org) > > === Nominated Mentors === > > * Luciano Resende (lresende at apache dot org) > * Thomas Weise (thw at apache dot org > * Kishore Gopalakrishna (kishoreg at apache dot org) > * Suneel Marthi (smarthi at apache dot org) > > === Sponsoring Entity === > > The Incubator PMC --------------------------------------------------------------------- To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org For additional commands, e-mail: general-h...@incubator.apache.org
