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WHEREAS, the Project Management Committee of the Apache HAWQ project has arrived at a consensus to recommend moving the project to the Attic; and WHEREAS, the Board of Directors deems it no longer in the best interest of the Foundation to continue the Apache HAWQ project due to inactivity; NOW, THEREFORE, BE IT RESOLVED, that the Apache HAWQ project is hereby terminated; and be it further RESOLVED, that the Attic PMC be and hereby is tasked with oversight over the software developed by the Apache HAWQ Project; and be it further RESOLVED, that the office of "Vice President, Apache HAWQ" is hereby terminated; and be it further RESOLVED, that the Apache HAWQ PMC is hereby terminated. Special Order 7B, Terminate the Apache HAWQ Project, was approved by Unanimous Vote of the directors present.
## Description: The mission of Apache HAWQ is the creation and maintenance of software related to a cloud native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop. ## Project Status: Current project status: given there were little or no activity in last few months, it is time to consider moving Apache HAWQ project to the Attic and dissolving the PMC accordingly. Currently, there are some ongoing discussions about the retirement of Apache HAWQ project in @private and @dev mail lists. Issues for the board: need help from board to guide Apache HAWQ project through the process of its retirement. ## Membership Data: Apache HAWQ was founded 2018-08-15 (6 years ago). There are currently 69 committers and 46 PMC members in this project. The Committer-to-PMC ratio is 3:2. Community changes, past quarter: No new PMC members. Last addition was Wan Chiyang on 2022-01-25. No new committers. Last addition was Wan Chiyang on 2021-02-20. ## Project Activity: 3.0.0.0 was released on 2021-08-18. There were no commit in last 6 months and no release in last 3 years. ## Community Health: Overall community health is not good as there are no activities given the inactivity of the project.
## Description: The mission of Apache HAWQ is the creation and maintenance of software related to a cloud native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop. ## Project Status: Current project status: given there were little or no activity in last few months, it is time to consider moving Apache HAWQ project to the Attic and dissolving the PMC accordingly. Currently, there are some ongoing discussions about the retirement of Apache HAWQ project in @private and @dev mail lists. Issues for the board: need help from board to guide Apache HAWQ project through the process of its retirement. ## Membership Data: Apache HAWQ was founded 2018-08-15 (6 years ago). There are currently 69 committers and 46 PMC members in this project. The Committer-to-PMC ratio is 3:2. Community changes, past quarter: - No new PMC members. Last addition was Wan Chiyang on 2022-01-25. - No new committers. Last addition was Wan Chiyang on 2021-02-20. ## Project Activity: 3.0.0.0 was released on 2021-08-18. There were no commit in last 6 months and no release in last 3 years. ## Community Health: Overall community health is not good as there are no activities given the inactivity of the project.
@Willem: follow up with Attic process
## Description: The mission of Apache HAWQ is the creation and maintenance of software related to a cloud native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop ## Project Status: Current project status: there are no outstanding issues requiring board attention regarding project status. Issues for the board: there are no outstanding issues requiring board attention. ## Membership Data: Apache HAWQ was founded 2018-08-15 (6 years ago) There are currently 69 committers and 46 PMC members in this project. The Committer-to-PMC ratio is 3:2. Community changes, past quarter: - No new PMC members. Last addition was Wan Chiyang on 2022-01-25. - No new committers. Last addition was Wan Chiyang on 2021-02-20. ## Project Activity: 3.0.0.0 was released on 2021-08-18. There was offline discussion on new features to be added to Apache HAWQ. ## Community Health: Overall community health is good. We have been performing extensive outreach to related projects, in order to attract new contributors. Previously, there are about 50% of all PMCs being subscribed to the private mail list, now there are 43 out of 46 PMCs being subscribed to the private mail list, which is about 93% as a result of 43% increase.
@Willem: follow up with HAWQ PMC on submitting a report
No report was submitted.
No report was submitted.
## Description: The mission of Apache HAWQ is the creation and maintenance of software related to a cloud native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop. ## Project Status: Current project status: there are no outstanding issues requiring board attention regarding project status. Issues for the board: there are no outstanding issues requiring board attention. ## Membership Data: Apache HAWQ was founded 2018-08-15 (5 years ago) There are currently 69 committers and 46 PMC members in this project. The Committer-to-PMC ratio is 3:2. Community changes, past quarter: - No new PMC members. Last addition was Wan Chiyang on 2022-01-25. - No new committers. Last addition was Wan Chiyang on 2021-02-20. ## Project Activity: 3.0.0.0 was released on 2021-08-18. There was offline discussion on new features to be added to Apache HAWQ. ## Community Health: Overall community health is good. We have been performing extensive outreach to related projects, in order to attract new contributors. Previously, there are about 50% of all PMCs being subscribed to the private mail list, now there are 43 out of 46 PMCs being subscribed to the private mail list, which is about 93% as a result of 43% increase.
@Justin: follow up on current status of project
## Description: The mission of Apache HAWQ is the creation and maintenance of software related to a cloud native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop. ## Project Status: Current project status: there are no outstanding issues requiring board attention. ## Membership Data: Apache HAWQ was founded 2018-08-15 (5 years ago) There are currently 69 committers and 46 PMC members in this project. The Committer-to-PMC ratio is about 3:2. Community changes, past quarter: - No new PMC members. Last addition was Wan Chiyang on 2022-01-25. - No new committers. Last addition was Wan Chiyang on 2021-02-20. ## Project Activity: 3.0.0.0 was released on 2021-08-18. There was offline discussion on new features to be added to Apache HAWQ. ## Community Health: Overall community health is good. We have been performing extensive outreach to related projects, in order to attract new contributors. Previously, there are about 50% of all PMCs being subscribed to the private mail list, now there are 43 out of 46 PMCs being subscribed to the private mail list, which is about 93% as a result of 43% increase.
No report was submitted.
## Description: The mission of Apache HAWQ is the creation and maintenance of software related to a cloud native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop. ## Issues: There are no outstanding issues requiring board attention. Except that almost 50% of all PMCs not being subscribed to the private list. ## Membership Data: Apache HAWQ was founded 2018-08-15 (5 years ago) There are currently 69 committers and 46 PMC members in this project. The Committer-to-PMC ratio is 3:2. Community changes, past quarter: - No new PMC members. Last addition was Wan Chiyang on 2022-01-25. - No new committers. Last addition was Wan Chiyang on 2021-02-20. ## Project Activity: 3.0.0.0 was released on 2021-08-18. Below are recent features and fixes: 1) HAWQ-1855. Fix access to the uninitialized variable database 2) HAWQ-1854. Support GRANT/REVOKE ON ALL TABLES/SEQUENCES/FUNCTIONS IN SCHEMA ## Community Health: Overall community health is good. We have been performing extensive outreach to related projected, in order to attract new contributors. We'd like to take his opportunity to ask the board or others reading this report for guidance on how to make the PMCs subscribe to the private list.
## Description: The mission of Apache HAWQ is the creation and maintenance of software related to a cloud native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop ## Issues: There are no outstanding issues requiring board attention. Except that almost 50% of all PMCs not being subscribed to the private list. ## Membership Data: Apache HAWQ was founded 2018-08-15 (4 years ago) There are currently 69 committers and 46 PMC members in this project. The Committer-to-PMC ratio is 3:2. Community changes, past quarter: - No new PMC members. Last addition was Wan Chiyang on 2022-01-25. - No new committers. Last addition was Wan Chiyang on 2021-02-20. ## Project Activity: 3.0.0.0 was released on 2021-08-18. Below are recent features and fixes: 1) HAWQ-1853. aarch64 port changes 2) HAWQ-1852. Fix find_udf 3) HAWQ-1851. Fix early free on savedSeqServerHost 4) HAWQ-1850. Fix life cycle of PlannedStmt and its resource 5) HAWQ-1847. change default value of gp_max_plan_slice to 36 6) HAWQ-1849. tag gpfdist --version as SQL version() ## Community Health: Overall community health is good. We have been performing extensive outreach to related projects, in order to attract new contributors. We'd like to take this opportunity to ask the board or others reading this report for guidance on how to make the PMCs subscribe to the private list.
## Description: The mission of Apache HAWQ is the creation and maintenance of software related to a Cloud native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop ## Issues: There are no outstanding issues requiring board attention. Except that almost 50% of all PMCs not being subscribed to the private list. ## Membership Data: Apache HAWQ was founded 2018-08-15 (4 years ago) There are currently 69 committers and 46 PMC members in this project. The Committer-to-PMC ratio is 3:2. Community changes, past quarter: - No new PMC members. Last addition was Wan Chiyang on 2022-01-25. - No new committers. Last addition was Wan Chiyang on 2021-02-20. ## Project Activity: 3.0.0.0 was released on 2021-08-18. Below are recent features and bug fixes: 1) HAWQ-1848. add GPFDIST_APR_MEM_MAX_SIZE to limit memory pool of gpfdist 2) HAWQ-1847. add guc gp_max_plan_slice to limit number of plan slice 3) HAWQ-1846. fix core when reset non exist guc 4) HAWQ-1845. fix issue in check_standy_sync 5) HAWQ-1844. only init orca on QD side ## Community Health: Overall community health is good. We have been performing extensive outreach to related projects, in order to attract new contributors. We'd like to take this opportunity to ask the board or others reading this report for guidance on how to make the PMCs subscribe to the private list.
## Description: The mission of Apache HAWQ is the creation and maintenance of software related to a cloud native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop ## Issues: There are no issues requiring board attention. ## Membership Data: Apache HAWQ was founded 2018-08-15 (4 years ago) There are currently 69 committers and 46 PMC members in this project. The Committer-to-PMC ratio is 3:2. Community changes, past quarter: - No new PMC members. Last addition was Wan Chiyang on 2022-01-25. - No new committers. Last addition was Wan Chiyang on 2021-02-20. ## Project Activity: Recent release: 3.0.0.0 was released on 2021-08-18. ## Community Health: Overall community health is good. We have 6 issues opened in JIRA in past quarter, and corresponding 6 commits to fix them. Details below: 1) HAWQ-1842: add session_state.session_level_memory_consumption 2) HAWQ-1811: set hawq_rm_stmt_vseg_memory to 256mb by default 3) HAWQ-1841: LOG ERROR in multi-phase aggregation planning with CSQ 4) HAWQ-1840: fix memory leak in hdfs/hive protocol external table 5) HAWQ-1839: fix memory leak in hdfsprotocol_blocklocation 6) HAWQ-1838: fix attribute typmod for CREATE TABLE AS SELECT
## Description: The mission of Apache HAWQ is the creation and maintenance of software related to a cloud native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop ## Issues: There are no issues requiring board attention ## Membership Data: Apache HAWQ was founded 2018-08-15 (4 years ago) There are currently 69 committers and 46 PMC members in this project The Committer-to-PMC ratio is 3:2. Community changes, past quarter: - Wan Chiyang was added to the PMC on 2022-01-25 - No new committers. Last addition was Wan Chiyang on 2021-02-20 ## Project Activity: There are bunch of new features and bug fixes after 3.0.0.0 release: HAWQ-1836. correct to parse standby state when database is unaccessible HAWQ-1835. support comma delimited format option for external table HAWQ-1834. add options for native orc table creation HAWQ-1832. fix ORC bloom filter option HAWQ-1831. fix core issue when metadatacache disabled HAWQ-1830. decorate the output of gp_enable_explain_allstat HAWQ-1829. orc_enable_filter_pushdown should be dispatched to QE ## Community Health: 1. 7 issues are opened and then closed, 11 commits in past quarter 2. Add PMC member Chiyang Wan to PMC Roster of Apache HAWQ Committee 3. Try to make PMC members subscribing private mail list
## Description: The mission of Apache HAWQ is the creation and maintenance of software related to a cloud native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop ## Issues: There are no issues requiring board attention. ## Membership Data: Apache HAWQ was founded 2018-08-15 (3 years ago) There are currently 69 committers and 46 PMC members in this project. The Committer-to-PMC ratio is roughly 3:2. Community changes, past quarter: - No new PMC members. Last addition was Chiyang on 2021-01-01. - No new committers. Last addition was Wan Chiyang on 2021-02-20. ## Project Activity: 1. 3.0.0.0 was released on 2021-08-18 and now we are working on 3.1.0.0 release. 2. the recent major changes including: 1) improve resource management for analyze/copy/UDF, etc. 2) improve upgrade scripts for HAWQ. 3) enable plperl by default. 4) support multiple location for readable ext HDFS table. 5) enable heap table for HAWQ. 6) improve proxy query dispatcher. 7) fix bug for interconnect, pg_dump, regex, etc. ## Community Health: 1. Bunch of new features and bug fixes are committed, i.e., there are 25 issues and pr opened and closed in past quarter. 2. New PMC members are introduced to Apache HAWQ community.
## Description: The mission of Apache HAWQ is the creation and maintenance of software related to a Hadoop native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop ## Issues: There are no issues requiring board attention. ## Membership Data: Apache HAWQ was founded 2018-08-15 (3 years ago) There are currently 69 committers and 45 PMC members in this project. The Committer-to-PMC ratio is roughly 3:2. Community changes, past quarter: - No new PMC members. Last addition was Amy Bai on 2018-08-15. - No new committers. Last addition was Chiyang Wan on 2021-02-20. ## Project Activity: 3.0.0.0 was released on 2021-08-18: 1) pluggable storage framework; 2) new design and implementation of dispatcher; 3) improvement for partitioned table. ## Community Health: 1. The project is active as the scope of 3.0.0.0 release includes a bunch of new features and bug fixes: 1) pluggable storage framework which enable us to support a new data source by writing a few interface functions; 2) new design and implementation of dispatcher which improve the scalability of the cluster; 3) improvement for partitioned table which boost its performance; 4) bug Fix: fix core dump when using locks; fix core dump in planner when multiple join alias are present; serialize the QueryResource in PlannedStmt; improve the error message when dead lock happens; fix memory leak in dispatcher. 2. there are some communications in private@hawq.apache.org regarding 3.0.0.0 release; dev@hawq.apache.org had a 480% increase in traffic in the past quarter ; issues@hawq.apache.org had a 740% increase in traffic in the past quarter. 3. for 3.0.0.0 release, 16 issues opened and 14 issues closed in JIRA; 17 commits in the past quarter; 2 code contributors in the past quarter; 10 PRs opened and then closed on GitHub, past quarter (1000% increase). 4. for next release, the commits are continuously checked in.
## Description: HAWQ is a Hadoop native SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. ## Issues: There are no issues requiring board attention. ## Membership Data: Apache HAWQ was founded 2018-08-15 (3 years ago) There are currently 69 committers and 45 PMC members in this project. The Committer-to-PMC ratio is roughly 3:2. Community changes, past quarter: - No new PMC members. Last addition was Amy Bai on 2018-08-15. - No new committers. Last addition was Wan Chiyang on 2021-02-20. ## Project Activity: Last release was Apache HAWQ 2.4.0.0 release on September 25, 2018. ## Community Health: 1. One of Apache HAWQ committer was invited to give a lecture on HAWQ development in Peking University. 2. HAWQ contributors attended SIGMOD 2021 in July, Xi'an, Shaanxi and communicated with researchers. 3. To make HAWQ more popular, there will be a joint effort with Nanchang University to give a seminar on HAWQ there.
## Description: HAWQ is a Hadoop native SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. ## Issues: None. ## Membership Data: Apache HAWQ was founded 2018-08-15 (3 years ago) There are currently 70 committers and 45 PMC members in this project. The Committer-to-PMC ratio is roughly 3:2. Community changes, past quarter: - No new PMC members. Last addition was Amy Bai and Kevin Monroe on 2018-04-24. - Chiyang Wan was added as committer on 2021-02-26. - Apache China raised an event in community to help contributers and committers hunting jobs as well as help domestic and overseas companies finding candidates, Feburary 26th, 2021. ## Project Activity: 1) Features - HAWQ-1779. Add GitHub Action for building on macOS - HAWQ-1780. Add GitHub Action Step to Test against Running Instance - HAWQ-1781. Add Github Action Sanity Test - HAWQ-1782. Fix failed to read EXTERNAL TABLE of GPFDIST protocol - HAWQ-1783. Add GitHub Action Workflow for Build on Linux - HAWQ-1784. Fix TestCreateTable depends on GUC setting - HAWQ-1785. Fix HDFS metadata mismatch in GitHub Action - HAWQ-1787. Refactor notice in pre-built toolchain - HAWQ-1788. set default value for dfs.domain.socket.path - HAWQ-1789. Make GitHub Workflow init script idempotent 2) Bug fixes: - HAWQ-1787. Fix travis-CI ## Community Health: - 11 issues opened in JIRA, past quarter - 11 issues closed in JIRA, past quarter - 11 commits in the past quarter Overall status of the project is healthy.
## Description: HAWQ is a SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop and Cloud. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. ## Issues: There are no issues requiring board attention. ## Membership Data: Apache HAWQ was founded 2018-08-15 (2 years ago) There are currently 68 committers and 45 PMC members in this project. The Committer-to-PMC ratio is roughly 3:2. Community changes, past quarter: - No new PMC members. Last addition was Amy Bai on 2018-08-15. - No new committers. Last addition was Stephen Tuyu on 2019-08-23. ## Project Activity: - Recent release: 2.4.0.0 was released on 2018-09-21 - Activity: 2020 PostgreSQL Conference China ## Community Health: Overall community health is action required. The development of Apache HAWQ is pretty good in the past quarter, with 213% increase in the issue traffic, 200% increase in the opened JIRA, and 400% increase in the closed JIRA. The reason is that we focused on the new features and facilities which were added to the project recently. However, we need to be more active in the community. Such as discuss and draft the roadmap, plan the new releases, have more interaction in the dev@hawq.apache.org, make more more committers and PMC members in the project.
## Description: HAWQ is a SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop and Cloud. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. ## Issues: None ## Membership Data: Apache HAWQ was founded 2018-08-15 (2 years ago) There are currently 68 committers and 45 PMC members in this project. The Committer-to-PMC ratio is roughly 3:2. Community changes, past quarter: - No new PMC members. Last addition was Amy Bai on 2018-08-15. - No new committers. Last addition was Stephen Tuyu on 2019-08-23. ## Project Activity: 1) Discuss the plan and scope for release 2.5.0.0: o orc format support o pluggable storage support o improve memory management for orc format o add resource enforcement, et al to Apache HAWQ o improvement for memory management module o improvement for partitioned tables o nested UDF can be run on segment 2) Bug fixes: o Fix core dump for UDF debug utility 3) Others: o A joint effort from Apache HAWQ community and Department of Computer Science, PKU, to provide an open source program to open source community. o Apache HAWQ integration with BI tool Fanruan, July 2020. ## Last release: Last release was Apache HAWQ 2.4.0.0 release on September 25, 2018
No report was submitted.
No report was submitted.
@Justin: pursue a roll call for HAWQ
Apache HAWQ Board report for July 2020. ## Description: HAWQ is a Hadoop native SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. ## Issues: None ## Activity: 1) working on the plan of release 2.5.0.0: o orc format support o pluggable storage support o improve memory management for orc format o add resource enforcement, et al to Apache HAWQ o improvement for memory management module o improvement for partitioned tables o nested UDF can be run on segment 2) Bug fixes ## Last release: Last release was Apache HAWQ 2.4.0.0 release on September 25, 2018 ## PMC changes: Last PMC addition was Amy Bai, Kevin Monroe on April 24, 2018, Currently 36 PMC members ## Committer base changes: Last committer Ziming Wang, and Yu Tu on August 23rd, 2019, Currently 47 committers
## Description: HAWQ is a Hadoop native SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. ## Issues: None ## Activity: 1) Discuss the plan and scope for release 2.5.0.0: o orc format support o pluggable storage support o improve memory management for orc format o add resource enforcement, et al to Apache HAWQ o improvement for memory management module o improvement for partitioned tables o nested UDF can be run on segment 2) Bug fixes: o Datalocality improvement o Add facility to debug UDF 3) Talks: - April 2nd, 2020, Oushu and Slidestalk held a joint online event in which Zhenglin Tao introduced the daily life of an apache hawq committer. In the talk, he told the history of Apache HAWQ, its advantages, and then comparison with other databases. Also, he showed how to commit code, conduct test, and do a release, as well as answer users' question in the HAWQ community. ## Last release: Last release was Apache HAWQ 2.4.0.0 release on September 25, 2018 ## PMC changes: Last PMC addition was Amy Bai, Kevin Monroe on April 24, 2018, Currently 36 PMC members ## Committer base changes: Last committer Ziming Wang, and Yu Tu on August 23rd, 2019, Currently 47 committers
No report was submitted.
Apache HAWQ Board report for January 2020. ## Description: HAWQ is a Hadoop native SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. ## Issues: None ## Activity: 1) Discuss the plan and scope for release 2.5.0.0: o orc format support o pluggable storage support o improve memory management for orc format o add resource enforcement, et al to Apache HAWQ o improvement for memory management module o nested UDF can be run on segment 2) Talks: - InfoQ interview (Yi Jin). October 30th, 2019. The interview video has been viewed more than 100,000 times on the Internet - Technical development and its application of HAWQ in China. Speaker: Zhenglin Tao. November 5th, 2019 - HAWQ technology sharing in Annual PostgreSQL conference in China. Speaker: Ruilong Huo. December 1st, 2019. ## Last release: Last release was Apache HAWQ 2.4.0.0 release on September 25, 2018 ## PMC changes: Last PMC addition was Amy Bai Kevin Monroe on April 24, 2018, Currently 36 PMC members ## Committer base changes: Last committer Ziming Wang, and Yu Tu on August 23rd, 2019, Currently 47 committers
Apache HAWQ Board report for October 2019. ## Description: HAWQ is a Hadoop native SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. ## Issues: None ## Activity: 1) Added INSERT and SELECT functionality for ORC, now ORC is fully supported. 2) Talks: - On July 20th, the famous domestic big data media InfoQ has an interview with Dr. Chang Lei on the development of HAWQ in China. Great help for the communication and influence of HAWQ, as well as the development of the community. - Dr. Jin Yi, the core developer of HAWQ, launched the HAWQ introductory series of tutorials in China to help more users understand HAWQ and study HAWQ. The first one is available on October 9th. - On October 23rd, HAWQ user Xueyin Wang conducted performance tests on HAWQ and similar products in the actual combat environment. HAWQ complete TPC-H support and super performance have left a deep impression on users during this test. ## PMC changes: None ## Committer base changes: New committer Ziming Wang, and Yu Tu Best regards, Ruilong Huo
## Description: HAWQ is a Hadoop native SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. ## Issues: None ## Activity: 1) Add docker of common, plan, storage compile for ORC 2) Support table CREATION and DROP functionality for ORC 3) In progress of supporting INSERT and SELECT functionality for ORC 4) Talks: - Introduction and implementation of pluggable storage framework in Apache HAWQ, Second Apache HAWQ meetup of year 2019, April 27, 2019. (Speaker: Huo Ruilong) - Application of pluggable storage framework in Apache HAWQ, Second Apache HAWQ meetup of year 2019, April 27, 2019. (Speaker: Huo Ruilong) - Using Apache HAWQ to build big data platform in Big Tree Finance Ltd., HAWQ Fans Club, June 28, 2019. (Zhao Chao) ## PMC changes: None ## Committer base changes: None
## Description: HAWQ is a Hadoop native SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. ## Issues: None ## Activity: 1) Adjust and finalize the scope of 2.5.0.0 release. The features will be included in the 2.5.0.0 release are: - New Feature: Add common library and its unit test to support ORC. - New Feature: Add plan library and its unit test to support ORC. - New Feature: Add storage library and its unit test to support ORC. - New Feature: Add ORC using pluggable storage framework. - New Feature: Add feature test for ORC format. 2) Finish common, plan, storage and their unit test for ORC support 3) Talks: - Apache HAWQ: The Next Generation Cloud Database, First Apache HAWQ meetup of year 2019, March 23, 2019. (Speaker: Chang Lei) - Apache Application in Finance, First Apache HAWQ meetup of year 2019, March 23, 2019. (Speaker: Tang Qiang) - HAWQ Application and Best Practice, First Apache HAWQ meetup of year 2019, March, 2019. (Speaker: Wang Xueying) ## PMC changes: None ## Committer base changes: Nonne ## Releases: Last release was 2.4.0.0 on Sep 23, 2018
## Description: HAWQ is a Hadoop native SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. ## Issues: None ## Activity: 1) In progress of adding ORC support for 2.5.0.0 release. - New Feature: Support write ORC storage format. - Bug fixes. 2) Talks: - FastCompany 2018: Innovation by Design Awards - China Electronic Chamber of Commerce 2018 - China Software Conference 2018: HAWQ won the excellent database of year awards and enclosed in book <<Data Wing>> ## PMC changes: Last PMC addition was Amy Bai Kevin Monroe on April 24, 2018, Currently 36 PMC members ## Committer base changes: Last committer addition was Shubham Sharma on April 25, 2018, Currently 45 committers ## Releases: Last release was 2.4.0.0 on Sep 23, 2018
## Description: HAWQ is a Hadoop native SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. ## Issues: None ## Activity: 1) Finalize the scope of 2.5.0.0 release community. The features will be included in the 2.5.0.0 release are: - New Feature: Support DDL for ORC as a native file format. - New Feature: Support write ORC storage format. - Bug fixes. 2) Finish part of feature for ORC support 3) Talks: - Apache HAWQ Roadmap, The 17th North East Asia OSS Promotion Forum (Speaker: Chang Lei) - New Data warehouse & AI, Data Technology Carnival 2018 (Speaker: Yang Zhe) - AI Anyone, World of Tech 2018 (Speaker: Liu Dawei) - Intel Roundtable Seminar 2018 (Attendee: Song Yixu) ## PMC changes: Last PMC addition was Amy Bai Kevin Monroe on April 24, 2018, Currently 36 PMC members ## Committer base changes: Last committer addition was Shubham Sharma on April 25, 2018, Currently 45 committers ## Releases: Last release was 2.4.0.0 on Sep 23, 2018
No report was submitted.
@Shane: pursue a report for HAWQ
## Description:
HAWQ is a Hadoop native SQL query engine that combines the key technological
advantages of MPP database with the scalability and convenience of Hadoop.
HAWQ reads data from and writes data to HDFS natively.
HAWQ delivers industry-leading performance and linear scalability. It
provides users the tools to confidently and successfully interact with
petabyte range data sets. HAWQ provides users with a complete, standards
compliant SQL interface.
## Issues:
None
## Activity:
1) The community released 2.4.0.0. Jiali YAO volunteered as the next release
manager and the team is planning a new release. The features in the 2.4.0.0
release are:
- New Feature: Pluggable Vectorized Execution Engine on HAWQ.
- New Feature: Support Runtime Filter for HAWQ local hash join.
2) Talks:
- The way to Apache TLP - HAWQ practices, COSCon 2018 (coming talk,
Speaker: Lei Chang)
- Apache HAWQ on Kubernetes: Bring SQL on Hadoop to Cloud, ApacheCon
2018
(Speaker: Ivan Weng, Wen Lin)
## PMC changes:
Last PMC addition was Amy Bai Kevin Monroe on April 24, 2018, Currently 36
PMC members
## Committer base changes:
Last committer addition was Shubham Sharma on April 25, 2018, Currently 45
committers
## Releases: Last release was 2.4.0.0 on Sep 23, 2018
## Description:
HAWQ is an advanced enterprise SQL on Hadoop analytic engine built around a
robust and high-performance massively-parallel processing (MPP) SQL engine
evolved from Greenplum Database.
## Issues:
None
## Activity:
1) The community is actively working on 2.4.0.0 release and target to be
released in Oct. Radar is serving as the RM. Currently we see a good progress
being made. The major features included in this release are:
- New Feature: Pluggable Vectorized Execution Engine on HAWQ.
- New Feature: Support Runtime Filter for HAWQ local hash join.
2) Coming community talks:
- The way to Apache TLP - HAWQ practices, COSCon 2018 (Speaker: Lei Chang)
- Apache HAWQ on Kubernetes: Bring SQL on Hadoop to Cloud, ApacheCon 2018
(Speaker: Ivan Weng, Wen Lin)
## Mailing list & JIRA activity in last three months:
- dev@hawqapache.org: 100 emails sent to list
- JIRA: 15 Issues Opened, 10 issues Closed/Resolved
## PMC changes:
Last PMC addition was Amy Bai Kevin Monroe on April 24, 2018, Currently 36 PMC
members
## Committer base changes:
Last committer addition was Shubham Sharma on April 25, 2018, Currently 45
committers
## Releases: Last release was 2.3.0.0 on Mar 21, 2018
WHEREAS, the Board of Directors deems it to be in the best interests of the Foundation and consistent with the Foundation's purpose to establish a Project Management Committee charged with the creation and maintenance of open-source software, for distribution at no charge to the public, related to a Hadoop native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop. NOW, THEREFORE, BE IT RESOLVED, that a Project Management Committee (PMC), to be known as the "Apache HAWQ Project", be and hereby is established pursuant to Bylaws of the Foundation; and be it further RESOLVED, that the Apache HAWQ Project be and hereby is responsible for the creation and maintenance of software related to a Hadoop native SQL query engine that combines the key technological advantages of an MPP database with the scalability and convenience of Hadoop; and be it further RESOLVED, that the office of "Vice President, Apache HAWQ" be and hereby is created, the person holding such office to serve at the direction of the Board of Directors as the chair of the Apache HAWQ Project, and to have primary responsibility for management of the projects within the scope of responsibility of the Apache HAWQ Project; and be it further RESOLVED, that the persons listed immediately below be and hereby are appointed to serve as the initial members of the Apache HAWQ Project: * Alan Gates <gates@apache.org> * Alexander Denissov <adenissov@apache.org> * Amy Bai <abai@apache.org> * Atri Sharma <atri@apache.org> * Bhuvnesh Chaudhary <bhuvnesh2703@apache.org> * Bosco <bosco@apache.org> * Chunling Wang <wangchunling@apache.org> * David Yozie <yozie@apache.org> * Ed Espino <espino@apache.org> * Entong Shen <entong@apache.org> * Foyzur Rahman <foyzur@apache.org> * Goden Yao <godenyao@apache.org> * Gregory Chase <gregchase@apache.org> * Hong Wu <xunzhang@apache.org> * Hongxu Ma <interma@apache.org> * Hubert Zhang <hubertzhang@apache.org> * Ivan Weng <iweng@apache.org> * Jesse Zhang <jz@apache.org> * Jiali Yao <jyao@apache.org> * Jun Aoki <jaoki@apache.org> * Kavinder Dhaliwal <kavinder@apache.org> * Lav Jain <lavjain@apache.org> * Lei Chang <lei_chang@apache.org> * Lili Ma <lilima@apache.org> * Lirong Jian <jian@apache.org> * Lisa Owen <lisao@apache.org> * Ming Li <mli@apache.org> * Mohamed Soliman <msoliman@apache.org> * Newton Alex <nalex@apache.org> * Noa Horn <nhorn@apache.org> * Oleksandr Diachenko <odiachenko@apache.org> * Paul Guo <paulguo@apache.org> * Radar Da Lei <rlei@apache.org> * Roman Shaposhnik <rvs@apache.org> * Ruilong Huo <huor@apache.org> * Shivram Mani <shivram@apache.org> * Shubham Sharma <outofmemory@apache.org> * Tushar Pednekar <tushar_pednekar@apache.org> * Venkatesh Raghavan <vraghavan78@apache.org> * Vineet Goel <vvineet@apache.org> * Wen Lin <wlin@apache.org> * Xiang Sheng <xsheng@apache.org> * Yi Jin <yjin@apache.org> * Zhanwei Wang <wangzw@apache.org> * Zhenglin Tao <ztao1987@apache.org> NOW, THEREFORE, BE IT FURTHER RESOLVED, that Lei Chang be appointed to the office of Vice President, Apache HAWQ, to serve in accordance with and subject to the direction of the Board of Directors and the Bylaws of the Foundation until death, resignation, retirement, removal or disqualification, or until a successor is appointed; and be it further RESOLVED, that the initial Apache HAWQ PMC be and hereby is tasked with the creation of a set of bylaws intended to encourage open development and increased participation in the Apache HAWQ Project; and be it further RESOLVED, that the Apache HAWQ Project be and hereby is tasked with the migration and rationalization of the Apache Incubator HAWQ podling; and be it further RESOLVED, that all responsibilities pertaining to the Apache Incubator HAWQ podling encumbered upon the Apache Incubator Project are hereafter discharged. Special Order 7B, Establish the Apache HAWQ Project, was approved by Unanimous Vote of the directors present.
HAWQ is an advanced enterprise SQL on Hadoop analytic engine built around a
robust and high-performance massively-parallel processing (MPP) SQL engine
evolved from Greenplum Database.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards graduation:
Nothing at this time.
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be aware
of?
Nothing urgent at this time.
How has the community developed since the last report?
1. Conference Talks :
* HAWQ for data scientists, Shanghai CIO forum (Speaker: Lei Chang, June
23, 2018)
2. "Graduate Apache HAWQ (incubating) as a TLP" discussion was started:
https://lists.apache.org/thread.html/67a2d52ef29cbf9e93d8050ed0193cc110a91996
2dd92f8436b343b7@%3Cdev.hawq.apache.org%3E
The followings is the content of the thread:
With the 2.3.0.0-incubating release officially out, the Apache HAWQ
community and its mentors believe it is time to consider graduation to the
TLP:
https://lists.apache.org/thread.html/b4a0b5671ce377b3d51c9b7
ab00496a1eebfcbf1696ce8b67e078c64@%3Cdev.hawq.apache.org%3E
Apache HAWQ entered incubation in September of 2015, since then, the HAWQ
community learned a lot about how to do things in Apache ways. Now we have
a healthy and engaged community, ready to help with all questions from the
HAWQ community. We delivered four releases including two binary releases,
now we can do self-driving releases in good cadence. The PPMC has
demonstrated a good understanding of growing the community by electing 12
individuals as committers and PPMC members. The PPMC addressed the maturity
issues one by one followed by Apache Project Maturity Model, currently all
the License and IP issues are resolved. This demonstrated our understanding
of ASF's IP policies.
All in all, I believe this project is qualified as a true TLP and we should
recognize this fact by formally awarding it such a status. This thread
means to open up the very same discussion that we had among the mentors and
HAWQ community to the rest of the IPMC. It is a DISCUSS thread so feel free
to ask questions.
To get you all going, here are a few data points which may help:
Project status:
http://incubator.apache.org/projects/hawq.html
Project website:
http://hawq.incubator.apache.org/
Project documentation:
http://hawq.incubator.apache.org/docs/userguide/2.3.0.0-inc
ubating/overview/HAWQOverview.html
http://hawq.apache.org/#download
Maturity assessment:
https://cwiki.apache.org/confluence/display/HAWQ/ASF+Maturity+Evaluation
DRAFT of the board resolution is at the bottom of this email
Proposed PMC size: 45 members
Total number of committers: 45 members
PMC affiliation (* indicated chair):
Pivotal (20)
* Oushu (7)
Amazon (3)
Hashdata (2)
Autonomic (1)
Confluent (1)
Datometry (1)
Hortonworks (1)
Microsoft (1)
PETUUM (1)
Privacera (1)
Qubole (1)
Snowflake (1)
State Street (1)
Unifi (1)
Visa (1)
ZEDEDA (1)
1549 commits on develop
1375 PR”s on GitHub
63 contributors across all branches
1624 issues created
1350 issues resolved
dev list averaged ~53 msgs/month over last 12 months
user list averaged ~6 msgs/month over last 12 months
129 unique posters
committer affiliations:
active
pivotal.io
oushu.io
hashdata.cn
occasional
amazon.com
autonomic.ai
confluent.io
datometry.com
hortonworks.com
microsoft.com
petuum.com
privacera.com
qubole.com
snowflake.net
statestreet.com
unifisoftware.com
visa.com
zededa.com
How would you assess the podling's maturity?
Please feel free to add your own commentary.
[ ] Initial setup
[ ] Working towards first release
[ ] Community building
[X] Nearing graduation
[ ] Other:
Date of last release:
2018-03-12, Apache HAWQ 2.3.0.0
When were the last committers or PPMC members elected?
1) Lav Jain: April 5, 2018
2) Shubham Sharma: April 5, 2018
Signed-off-by:
[X](hawq) Alan Gates
Comments:
[ ](hawq) Justin Erenkrantz
Comments:
[ ](hawq) Thejas Nair
Comments:
[X](hawq) Roman Shaposhnik
Comments:
IPMC/Shepherd notes:
HAWQ is an advanced enterprise SQL on Hadoop analytic engine built around a
robust and high-performance massively-parallel processing (MPP) SQL engine
evolved from Greenplum Database.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards graduation:
1. Continue to improve the project's release cadence. To this end we plan on
expanding automation services to support increased developer participation.
(HAWQ-127)
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be aware
of?
Nothing urgent at this time.
How has the community developed since the last report?
1. Conference Talks :
* HAWQ on Microsoft Azure Cloud. Microsoft Incubator Talk (Speaker: Lei
Chang, Mar 21, 2018)
2. Two committer candidates passed the voting process:
1) Shubham SHARMA 2) Lav JAIN
How has the project developed since the last report?
1. HAWQ 2.3 released. It includes the following features.
1) New Feature: HAWQ Core supports plugable external storage framework. 2)
New Feature: HAWQ Ranger supports RPS HA. 3) New Feature: HAWQ Ranger
supports Kerberos authentication. 4) New Feature: HAWQ Core supports HDFS
TDE (Transparent Data Encryption) through libHdfs3. 5) Licenses: Fix PXF
license files located in PXF jar files. 6) Licenses: Check Apache HAWQ
mandatory libraries to match LC20, LC30 license criteria. 7) Build: Release
build project 8) Bug fixes.
Project page link:
https://cwiki.apache.org/confluence/display/HAWQ/Apache+HAWQ+2.3.0.0-incubating+Release
2. HAWQ 2.4 release plan was proposed.
1) New Feature: Pluggable Vectorized Execution Engine on HAWQ. 2) New
Feature: Support Runtime Filter for HAWQ local hash join. 3) New Feature:
Support accessing Hive table data by the new Pluggable Storage Framework. 4)
Bug fixes.
Project page link:
https://cwiki.apache.org/confluence/display/HAWQ/Apache+HAWQ+2.4.0.0-incubating+Release
How would you assess the podling's maturity?
Please feel free to add your own commentary.
[ ] Initial setup
[ ] Working towards first release
[ ] Community building
[X] Nearing graduation
[ ] Other:
Date of last release:
2018-03-12, Apache HAWQ 2.3.0.0
When were the last committers or PPMC members elected?
1) Lav Jain: April 5, 2018 2) Shubham Sharma: April 5, 2018
Signed-off-by:
[X](hawq) Alan Gates
Comments:
[ ](hawq) Justin Erenkrantz
Comments:
[ ](hawq) Thejas Nair
Comments:
[X](hawq) Roman Shaposhnik
Comments:
HAWQ is an advanced enterprise SQL on Hadoop analytic engine built around a
robust and high-performance massively-parallel processing (MPP) SQL framework
evolved from Pivotal Greenplum Database.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards graduation:
1. Continue to improve the project's release cadence. To this end we plan on
expanding automation services to support increased developer participation.
(HAWQ-127) 2. Licenses: Check Apache HAWQ mandatory libraries to match LC20,
LC30 license criteria. (HAWQ-1512)
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be aware
of?
Nothing urgent at this time.
How has the community developed since the last report?
1. Conference Talks (2):
* The nature of cloud database. The 7th Data Technology Carnival (Speaker:
Lei Chang, Nov 17, 2017)
* New Data Warehouse: Apache HAWQ. 2017 Global Internet Technology Conference
(Speaker: Lei Chang, Nov 24, 2017)
2. Active contributions from approximately 20 different community contributors
since the last report.
3. Three committer candidates passed the voting process:
1) Amy BAI 2) ChunLing WANG 3) Hongxu MA
How has the project developed since the last report?
1. The scope of 2.3 release is finalized, and is under development
1) New Feature: HAWQ Ranger supports RPS HA. (Done) 2) New Feature: HAWQ
Ranger supports Kerberos authentication. (Done) 3) New Feature: HAWQ Core
supports plugable external storage framework. (Almost Done HAWQ-786) 4) New
Feature: HAWQ Core supports HDFS TDE (Transparent Data Encryption) through
libHdfs3. (Done, HAWQ-1193) 5) Licenses: Fix PXF license files located in
PXF jar files. (Done HAWQ-1496) 6) Licenses: Check Apache HAWQ mandatory
libraries to match LC20, LC30 license criteria. (Not started HAWQ-1512) 7)
Build: Release build project (On going HAWQ-127) 8) Bug fixes. (On going)
Project page link:
https://cwiki.apache.org/confluence/display/HAWQ/Apache+HAWQ+2.3.0.0-incubating+Release
2. The community discussed the future of PXF with the addition of the
pluggable storage feature: Pluggable storage formats and files systems vs. PXF
How would you assess the podling's maturity? Please feel free to add your own
commentary.
[ ] Initial setup
[ ] Working towards first release
[ ] Community building
[X] Nearing graduation
[ ] Other:
Date of last release:
2017-07-12, Apache HAWQ 2.2.0.0
When were the last committers or PPMC members elected?
1) Amy BAI: Nov 1, 2017 2) ChunLing WANG: Nov 1, 2017 3) Hongxu MA: Nov 4,
2017
Signed-off-by:
[X](hawq) Alan Gates
Comments:
[ ](hawq) Konstantin Boudnik
Comments:
[ ](hawq) Justin Erenkrantz
Comments:
[ ](hawq) Thejas Nair
Comments:
[X](hawq) Roman Shaposhnik
Comments:
HAWQ is an advanced enterprise SQL on Hadoop analytic engine built around a
robust and high-performance massively-parallel processing (MPP) SQL framework
evolved from Pivotal Greenplum Database.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards
graduation:
1. Continue to improve the project's release cadence. To this
end we plan on expanding automation services to support
increased developer participation.
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need
to be aware of?
Nothing urgent at this time.
How has the community developed since the last report?
1. Conference Talks (2):
* Big Data Technology Trends. China Big Data Industry Ecosystem Conference (Speaker: Lei Chang, August 2, 2017)
* Future Data Warehouse. China CIO Conference (Speaker: Lei Chang, Sep 16, 2017)
2. Active contributions from approximately 20 different community
contributors since the last report (July 2017).
3. Yi JIN volunteered as the release manager for 2.3 release.
How has the project developed since the last report?
1. Apache HAWQ 2.2.0.0 was released. HAWQ 2.2 is the first binary release.
Release information:
1) Release page:
https://cwiki.apache.org/confluence/display/HAWQ/Apache+HAWQ+2.2.0.0-incubating+Release
2) Issues/tasks fixed (80):
https://issues.apache.org/jira/issues/?filter=12339844
2. The scope of 2.3 release is finalized:
1) New Feature: HAWQ Ranger supports RPS HA. (Done)
2) New Feature: HAWQ Ranger supports Kerberos authentication. (Done)
3) New Feature: HAWQ Core supports plugable external storage framework. (On going HAWQ-786)
4) New Feature: HAWQ Core supports HDFS TDE (Transparent Data Encryption) through libHdfs3. (Done, HAWQ-1193)
5) Licenses: Fix PXF license files located in PXF jar files. (Not started HAWQ-1496)
6) Licenses: Check Apache HAWQ mandatory libraries to match LC20, LC30 license criteria. (Not started HAWQ-1512)
7) Build: Release build project (On going HAWQ-127)
8) Bug fixes. (On going)
Project page link: https://cwiki.apache.org/confluence/display/HAWQ/Apache+HAWQ+2.3.0.0-incubating+Release
3. Project mail list activity:
Between July 1, 2017 and Sep 25, 2017:
dev@hawq.apache.org & user@hawq.apache.org
155 emails sent
53 participants
How would you assess the podling's maturity?
Please feel free to add your own commentary.
[ ] Initial setup
[ ] Working towards first release
[ ] Community building
[X] Nearing graduation
[ ] Other:
Date of last release:
2017-07-12, Apache HAWQ 2.2.0.0
When were the last committers or PPMC members elected?
Podling committers (1) added:
Xiang Sheng (https://github.com/stanlyxiang), May 16, 2017
Signed-off-by:
[X](hawq) Alan Gates
Comments:
[ ](hawq) Konstantin Boudnik
Comments:
[ ](hawq) Justin Erenkrantz
Comments:
[ ](hawq) Thejas Nair
Comments:
[ ](hawq) Roman Shaposhnik
Comments:
Apache HAWQ is a Hadoop native SQL query engine that combines the
key technological advantages of MPP database with the scalability
and convenience of Hadoop. HAWQ reads data from and writes data
to HDFS natively. HAWQ delivers industry-leading performance and
linear scalability. It provides users the tools to confidently
and successfully interact with petabyte range data sets. HAWQ
provides users with a complete, standards compliant SQL
interface.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards
graduation:
1. Continue to improve the project's release cadence. To this
end we plan on expanding automation services to support
increased developer participation.
2. Continue to expand the community, by adding new contributors
and focusing on making sure that there's a much more robust
level of conversations and discussions happening around
roadmaps and feature development on the public dev mailing
list.
3. Starting with Apache HAWQ 2.2.0.0 release, the project will
expand release artifacts to include the delivery of
convenience binary artifacts. We expect the project to
significantly refine the binary release process in several
key areas. The team is limiting scope to HAWQ Core and PXF
components. The appropriate LICENSE, DISCLAIMER and NOTICE
files are included in the binary release artifacts.
FYI: The team has decided to move Ranger (optional
component) support into a subsequent binary release. It
remains supported in the source release.
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need
to be aware of?
Nothing urgent at this time.
How has the community developed since the last report?
1. Conference Talks (7):
* Introduction to latest technology in HAWQ 2.X, the 8th Database
Technology Conference China (Speaker: Lili Ma, Pivotal, May 13,
2017)
* "Podling Shark" lightning session, ApacheCon North America
2017, (Speaker: Aleksandr Diachenko and Alexander Denissov,
Pivotal, May 18, 2017)
* The Big Data Engine in Cloud Era, CSDN Cloud Computing
Technology Conference (Speaker: Zhenglin Tao, Oushu Inc, May
19, 2017)
* HAWQ Introduction. China International Big Data Industry Expo
2017 (Speaker: Lan Zhou, Oushu Inc, May 26, 2017)
* Extending Apache Ranger Authorization Beyond Hadoop: Review of
Apache Ranger Extensibility Framework & Case Study for
Integration with Apache Hawq, DataWorks Summit,
https://www.youtube.com/watch?v=6SE32zrgIAU (Speaker: Ramesh
Mani, Hortonworks & Alexander Denissov, Pivotal, June 13, 2017)
* Hawq Meets Hive - Querying Unmanaged Data, DataWorks Summit,
https://www.youtube.com/watch?v=sjlZJvHx1hM (Speaker: Shivram
Mani & Alex (Oleksandr) Diachenko, Pivotal, June 14, 2017)
* Apache HAWQ: Open Source MPP++ Database, The 12th China Open
Source World Summit, (Speaker: Lei Chang, Oushu Inc, June 21,
2017)
2. Active contributions from approximately 20 different community
contributors since the last report (April 2017).
3. The Open Source Greenplum Database community (http://greenplum.org)
is reviewing opportunities to leverage Apache HAWQ components.
Here is the initial GitHub Pull Request:
https://github.com/greenplum-db/gpdb/pull/2634
How has the project developed since the last report?
1. Apache HAWQ 2.2.0.0 release has passed PPMC vote. This
contains the initial convenience binary release. The release
has been sent to IPMC for voting.
FYI: The project's Apache HAWQ 2.2.0.0 release
manager (Ruilong Huo) represents Oushu Inc.
(http://www.oushu.io - HAWQ++ is the world's first MPP SQL
engine that can run native to the container cloud platform).
Release information:
1) Release page:
https://cwiki.apache.org/confluence/display/HAWQ/Apache+HAWQ+2.2.0.0-incubating+Release
2) Issues/tasks fixed (80):
https://issues.apache.org/jira/issues/?filter=12339844
2. Per project mentor guidance, the Apache Incubator logo has
been applied to the project's website (http://hawq.incubator.apache.org/)
and wiki (https://cwiki.apache.org/confluence/display/HAWQ/Apache+HAWQ+Home).
3. Per project mentor guidance, an incubator project logo was
created and voted on. It has been applied to the projet's wiki:
https://cwiki.apache.org/confluence/display/HAWQ/Apache+HAWQ+Home
4. To encourage more doc contributions, a discussions took place
on dev/user mail lists to recommend moving the HAWQ doc
repository (https://github.com/apache/incubator-hawq-docs
master branch) into the HAWQ source
repository (https://github.com/apache/incubator-hawq).
5. Project mail list activity:
Between Sat Apr 01 2017 and Fri Jun 30 2017:
dev@hawq.apache.org
337 emails sent
147 topics started
87 participants
user@hawq.apache.org
78 emails sent
24 topics started
35 participants
How would you assess the podling's maturity?
Please feel free to add your own commentary.
[ ] Initial setup
[ ] Working towards first release
[X] Community building
[X] Nearing graduation
[ ] Other:
Date of last release:
2017-02-28, Apache HAWQ 2.1.0.0
When were the last committers or PPMC members elected?
Podling committers (1) added:
Xiang Sheng (https://github.com/stanlyxiang), May 16, 2017
Signed-off-by:
[X](hawq) Alan Gates
Comments:
[ ](hawq) Konstantin Boudnik
Comments:
[ ](hawq) Justin Erenkrantz
Comments:
[ ](hawq) Thejas Nair
Comments:
[ ](hawq) Roman Shaposhnik
Comments:
Apache HAWQ is a Hadoop native SQL query engine that combines the key
technological advantages of MPP database with the scalability and convenience
of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ
delivers industry-leading performance and linear scalability. It provides
users the tools to confidently and successfully interact with petabyte range
data sets. HAWQ provides users with a complete, standards compliant SQL
interface.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards graduation:
1. Continue to improve the project's release cadence. To this end we
plan on expanding automation services to support increased
developer participation.
2. Continue to expand the community, by adding new contributors and
focusing on making sure that there's a much more robust level of
conversations and discussions happening around roadmaps and
feature development on the public dev mailing list.
3. Expand release artifacts to include the delivery of binary
artifacts. We expect the project to significantly refine the
binary release process in several key areas.
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be
aware of?
1. Nothing urgent at this time.
How has the community developed since the last report?
1. Two Meetups took place in Beijing, China:
* HAWQ Meetup (January 12, 2017)
- HAWQ2.X New Features - Yanqing Wen, Pivotal HAWQ Senior
Engineer
- HAWQ Elasticity - Huan Zhang, Pivotal HAWQ Senior Engineer
- Data Lake and HAWQ Integration - Wenbin Lu, EMC Big Data
Senior Engineer
* HAWQ Meetup (March 23, 2017)
- Apache HAWQ Exploration Step by Step - Configuration, Build,
Deployment and Debug by Xiang Sheng, Pivotal Software
Engineer
- Transaction Management in Apache HAWQ by Ming Li, Pivotal
Senior Software Engineer
- Max Compute - A SQL engine based on Apache HAWQ by Chen Xia,
Database Expert in Alibaba Cloud
2. A significant push by the dev community has been made to review
and merge the project's Pull Requests (PR). As of March 30, 2017,
eight of the nine open PRs have been opened in the last ten
days. The PR opened on Sep 2016 is targeted to be merged after
the Apache 2.2.0.0 release.
3. Community contribution highlight(s):
* Leveraging the extensible PXF design, a JDBC PXF plugin
was contributed by Devin Jia (github id: jiadexin). This
contribution came from the community and not from the
company which originally donated HAWQ to the ASF.
4. Recent porting efforts:
- Persistent Systems Engineers are actively engaging the dev
community on their HAWQ porting efforts to RHEL 7.1 on S390
platform.
- Ubuntu 16.04.2 LTS (Xenial Xerus) porting notes have been
published on dev list.
5. Ruilong Huo has volunteered to be the Release Manager (RM) for
the upcoming 2.2.0.0 release
How has the project developed since the last report?
1. Apache HAWQ 2.1.0.0 (source code only) has been released.
2. Apache HAWQ 2.2.0.0 release proposed (source code and first
binary release). This is the 3rd release as an incubating
project. The binaries will be Hadoop vendor agnostic providing
support for the Apache Bigtop 1.2.0 distribution.
Release page:
https://cwiki.apache.org/confluence/display/HAWQ/Apache+HAWQ+2.2.0.0-incubating+Release
Release hightlights:
* CentOS 7.x Support
* Ranger Integration
* PXF ORC Profile
* Bug Fixes
3. Paul Guo (paulguo@gmail.com - committer and recent HAWQ PPMC
member) is publishing (to dev email list) a regular HAWQ Graduation
update for the project.
* HAWQ graduation update (January, 17, 2017)
https://lists.apache.org/thread.html/cd37e2b48d4bbc9fe4a9cea47f8247a2a614fa9643171937db9568ed@%3Cdev.hawq.apache.org%3E
* Apache HAWQ graduation update (Mar 1st, 2017)
https://lists.apache.org/thread.html/3a1e454f8c706dd71b1690c3ae74a157ef42eefde2185c780e2a57a2@%3Cdev.hawq.apache.org%3E
4. The Apache HAWQ website has been updated:
* Provide clearer (more user-friendly) home page with good
access to downloadable release artifacts.
* The Apache HAWQ doc set is opened sourced and accessible
from website's nav bar.
5. Significant updates to the Apache HAWQ wiki:
* Add more community activities and recorded videos:
https://cwiki.apache.org/confluence/display/HAWQ/Community
* Add design documents for certain components:
https://cwiki.apache.org/confluence/display/HAWQ/Tech+Documents
How would you assess the podling's maturity?
Please feel free to add your own commentary.
[ ] Initial setup
[ ] Working towards first release
[X] Community building
[X] Nearing graduation
[ ] Other:
Date of last release:
2017-02-28
When were the last committers or PMC members elected?
Podling committers (3) added:
Lisa Owen: January 31, 2017
Jane Beckman: February 1, 2017
Kyle Dunn: March 2, 2017
PPMC member (1) added:
Paul Guo: March 10, 2017
Signed-off-by:
[X](hawq) Alan Gates
Comments:
[X](hawq) Konstantin Boudnik
Comments:
[ ](hawq) Justin Erenkrantz
Comments:
[ ](hawq) Thejas Nair
Comments:
[x](hawq) Roman Shaposhnik
Comments:
Podling seems to be a few months away from fulfilling all of the
graduation requirements.
IPMC/Shepherd notes:
johndament: The podling is extremely active, I'm not sure there's anything
left blocking them from graduation.
Apache HAWQ is a Hadoop native SQL query engine that combines the key
technological advantages of MPP database with the scalability and convenience
of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ
delivers industry-leading performance and linear scalability. It provides
users the tools to confidently and successfully interact with petabyte range
data sets. HAWQ provides users with a complete, standards compliant SQL
interface.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards graduation:
1. Expand the community, by adding new contributors and focusing on making
sure that there's a much more robust level of conversations and
discussions happening around roadmaps and feature development on the
public dev mailing list
2. Infrastructure migration: create Jenkins projects that build HAWQ
binary, source tarballs, and run feature tests including at least
installcheck-good tests for each commit (HAWQ-127).
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be aware
of?
Everything seems to be smooth, nothing urgent at this time.
How has the community developed since the last report?
1. The community becomes more open for discussion around the roadmap,
various features that committers are working on, infrastructure
enhancements for the project.
2. Two talks:
* The SQL-on-Hadoop engine that replaces traditional data warehouses:
HAWQ, China Open Source Conference Oct, 2016, Lei Chang
* Apache HAWQ on cloud: the easiest way to cloud from traditional data
warehouses, Big Data Technology Conferences, Dec, 2016, Lei Chang
3. Ed volunteered as an RM for the upcoming 2.1.0.0 release
4. Interesting discussions and work around Docker for HAWQ. HAWQ has an
account on docker hub: https://hub.docker.com/u/hawq/
How has the project developed since the last report?
1. Apache HAWQ 2.0.0.0 released.
2. HAWQ 2.1.0.0 release proposed:
https://cwiki.apache.org/confluence/display/HAWQ/HAWQ+Release+2.1.0.0-incubating+Release
* Critical HAWQ Register bug fixes
* Move HAWQ Ambari plugin to Apache HAWQ: HAWQ-1013 RESOLVED
* Introduction of the PXF ORC support
* Many bug fixes
Date of last release:
Oct 8, 2016
When were the last committers or PMC members elected?
Two committers added: Hong Wu and Paul Guo
Signed-off-by:
[X](hawq) Alan Gates
[ ](hawq) Konstantin Boudnik
[ ](hawq) Justin Erenkrantz
[ ](hawq) Thejas Nair
[X](hawq) Roman Shaposhnik
Apache HAWQ is a Hadoop native SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. HAWQ has been incubating since 2015-09-04. Three most important issues to address in the move towards graduation: 1. Produce our first Apache Release 2. Expand the community, by adding new contributors and focusing on making sure that there's a much more robust level of conversations and discussions happening around roadmaps and feature development on the public dev mailing list 3. Infrastructure migration: create Jenkins projects that build HAWQ binary, source tarballs, and run feature tests including at least installcheck-good tests for each commit (HAWQ-127). Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be aware of? Everything seems to be smooth, nothing urgent at this time. How has the community developed since the last report? 1. we have seen significant increase of communication and collaboration across the whole community in past 3 months. The community becomes more open for discussion around the roadmap, various features that committers are working on, infrastructure enhancements for the project. 2. One talk at trust cloud computing summit * Apache HAWQ: The leading SQL-on-Hadoop Query Engine. (http://www.cnii.com.cn/technology/img/4598.files/yicheng.html) 3. Two meetups: Data Science at Scale with HAWQ and MADlib and Hadoop * https://www.meetup.com/Data-Engineers-Guild/events/233974633/ * https://www.meetup.com/futureofdata-siliconvalley/events/232976650/ How has the project developed since the last report? 1. The release candidate (Apache HAWQ 2.0.0.0-incubating RC4) has been proposed and the voting process on the dev mailing list completed. The main target of the first release is to clear all IP related issues for HAWQ and this is a source code tarball only release. Full list of JIRAs fixed/related to the release: link <https://cwiki.apache.org/confluence/display/HAWQ/HAWQ+Release+2.0.0.0-incubat ing> 2. New features added include * snappy compression for AO tables * HAWQ register feature for registering data into HAWQ native tables * PXF - JSON support (https://issues.apache.org/jira/browse/HAWQ-178) Date of last release: We have not had a release yet. When were the last committers or PMC members elected? Add one committer in September: Kavinder Dhaliwal Signed-off-by: [ ](hawq) Alan Gates [x](hawq) Konstantin Boudnik [ ](hawq) Justin Erenkrantz [ ](hawq) Thejas Nair [X](hawq) Roman Shaposhnik Shepherd/Mentor notes: (rvs) Now that the first release of HAWQ has officially been published, I believe the community has unblocked itself and will be running in high gear. Looking forward to a cadence of releases and community expansion.
Apache HAWQ is a Hadoop native SQL query engine that combines the key
technological advantages of MPP database with the scalability and
convenience of Hadoop. HAWQ reads data from and writes data to HDFS
natively. HAWQ delivers industry-leading performance and linear
scalability. It provides users the tools to confidently and successfully
interact with petabyte range data sets. HAWQ provides users with a complete,
standards compliant SQL interface.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards graduation:
1. Produce our first Apache Release
2. Expand the community, by adding new contributors and focusing on making
sure that there's a much more robust level of conversations and
discussions happening around roadmaps and feature development on the
public dev mailing list
3. Infrastructure migration: create Jenkins projects that build HAWQ
binary, source tarballs, and run feature tests including at least
installcheck-good tests for each commit (HAWQ-127).
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be
aware of?
Everything seems to be smooth, nothing urgent at this time.
How has the community developed since the last report?
1. we have seen significant increase of communication and collaboration
across the whole community from last several weeks. The community
becomes more open for discussion around the roadmap, various features
that committers are working on, and infrastructure enhancements for the
project.
2. One meetup: Zeppelin meets MADlib & HAWQ
(https://www.youtube.com/watch?v=p8V10IukBes&list=PL62pIycqXx-Qf6EXu5FDxUgXW23BHOtcQ&index=6)
3. The PPMC was made aware of an erroneous use of Apache HAWQ (incubating)
trademark by a vendor doing research with an older, eponymous Pivotal
product. The PPMC is working with a vendor and ASF's VP of Branding to
resolve the issue.
How has the project developed since the last report?
1. The first release candidate has been proposed and it is under the
voting process on the dev mailing list
2. New features added include snappy compression for AO tables, HAWQ
register feature for registering data into HAWQ native tables
3. The build system has been simplified a lot by making some components as
optional (for example, pl/r, orca et al)
4. The community is consolidating the testing frameworks including
installcheck tests and gtest into gtest based framework.
5. Including the incubating disclaimer on Apache HAWQ website based on the
podling branding guidelines
Date of last release:
We have not had a release yet.
When were the last committers or PMC members elected?
No new committers/members from initial.
Signed-off-by:
[X](hawq) Alan Gates
[ ](hawq) Konstantin Boudnik
[ ](hawq) Justin Erenkrantz
[ ](hawq) Thejas Nair
[X](hawq) Roman Shaposhnik
Shepherd/Mentor notes:
Roman Shaposhnik:
I'm happy to report that the trademark violation incident was taken care
of by the offending party quite to the delight of HAWQ's PMC.
Apache HAWQ is a Hadoop native SQL query engine that combines the key
technological advantages of MPP database with the scalability and
convenience of Hadoop. HAWQ reads data from and writes data to HDFS
natively. HAWQ delivers industry-leading performance and linear
scalability. It provides users the tools to confidently and successfully
interact with petabyte range data sets. HAWQ provides users with a complete,
standards compliant SQL interface.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards graduation:
1. Produce our first Apache Release
2. Expand the community, by adding new contributors and focusing on making
sure that there's a much more robust level of conversations and
discussions happening around roadmaps and feature development on the
public dev mailing list
3. Infrastructure migration: create Jenkins projects that build HAWQ
binary, source tarballs, and run feature tests including at least
installcheck-good tests for each commit (HAWQ-127).
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be
aware of?
Everything seems to be smooth, nothing urgent at this time.
How has the community developed since the last report?
1. One HAWQ Nest community meeting (topic: GPORCA: Query Optimization as a
Service) Video: http://bit.ly/HAWQNest0223yt
2. The community shows pretty high activities. In Dev, there have been 816
messages on dev@/user@ in March 2016.
3. Got around 29 pull requests from contributors that are not in the
initial committer team.
4. GSoC 2016: 6 topics created for it.
5. FOSDEM 2016 event:
https://fosdem.org/2016/schedule/event/hpc_bigdata_hadoopsql/
https://s.apache.org/BYMR
How has the project developed since the last report?
1. Main features/improvements added include:
a) Hawq-473 Add fault reason and history into hawq catalog
b) HAWQ-404 Add sort during INSERT of append only row oriented
partition tables
c) HAWQ-558 Improve performance of truncate on small tables
d) HAWQ-532 HAWQ-580 HAWQ-587 Enhance the virtual segment number
selection method
e) HAWQ-551 Enhance explain analyze with more information on data
locality and resource manager
f) HAWQ-546 Enhance \d for HCatalog tables
g) HAWQ-144 Support HAWQ build on MAC
h) HAWQ-597 Add Travis CI(OSX) for MAC
i) Critical bug fixes.
2. 135 new JIRAs filed, 116 resolved (In Mar 2016)
3. 134 code commits (In Mar 2016)
Date of last release:
We have not had a release yet.
When were the last committers or PMC members elected?
No new committers/members from initial.
Signed-off-by:
[](hawq) Alan Gates
[](hawq) Konstantin Boudnik
[](hawq) Justin Erenkrantz
[](hawq) Thejas Nair
[X](hawq) Roman Shaposhnik
Shepherd/Mentor notes:
Justin Mclean (jmclean):
A couple on minor issues around communication on list and releases but
mentors are on top on it.
Apache HAWQ is a Hadoop native SQL query engine that combines the key
technological advantages of MPP database with the scalability and
convenience of Hadoop. HAWQ reads data from and writes data to HDFS
natively. HAWQ delivers industry-leading performance and linear
scalability. It provides users the tools to confidently and successfully
interact with petabyte range data sets. HAWQ provides users with a complete,
standards compliant SQL interface.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards graduation:
1. Produce our first Apache Release
2. Expand the community, increase dev list activity and adding new
contributors
3. Infrastructure migration: create Jenkins projects that build HAWQ
binary, source tarballs and docker images, and run feature tests
including at least installcheck-good tests for each commit (HAWQ-127).
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be
aware of?
Everything seems to be smooth, nothing urgent at this time.
How has the community developed since the last report?
1. One HAWQ Nest community meeting (topic: Data Federation with Apache
HAWQ Using the PXF Extension Framework)
Video: http://bit.ly/HAWQNest1217, Slides: http://bit.ly/HAWQNest1217ss
2. The community shows increasing activities. In Dev, there have
been 494 messages on dev@/user@, compared with 459 messages in Nov.
How has the project developed since the last report?
1. Main features/improvements added include:
a) Improve recovery performance during some exception cases (HAWQ-241,
HAWQ-232)
b) Support writable external table executing on a specified number of
virtual segment (HAWQ-293)
c) Improve HAWQ resource manager resource allocation algorithm and RPC
framework (HAWQ-234)
d) Support fault injector in 2.0 (HAWQ-288)
e) Clean up some IP and build related issues (HAWQ-277, HAWQ-186,
HAWQ-184, HAWQ-228)
f) Some key bug fixes for 2.0 Beta
2. 2.0 Beta RC2 was proposed
3. 98 new JIRAs filed, 59 resolved (In Dec 2015)
4. 82 code commits (In Dec 2015)
Date of last release:
We have not had a release yet.
When were the last committers or PMC members elected?
No new committers/members from initial.
Signed-off-by:
[X](hawq) Alan Gates
[x](hawq) Konstantin Boudnik
[x](hawq) Justin Erenkrantz
[](hawq) Thejas Nair
[x](hawq) Roman Shaposhnik
Shepherd/Mentor notes:
Justin Erenkrantz:
There has been good progress on improving the licensing situation
(HAWQ-271) as well as conversations about what it means to be a
contributor (yielding
https://cwiki.apache.org/confluence/display/HAWQ/Becoming+a+committer).
All good and healthy so far.
Konstantin Boudnik (cos):
Same comment as for Geode: the report is almost copy-cut from one another
(if not in the letter, but in the spirit). Did you guys had anything worth
mentioning besides of new features and bug fixes? Like Justin mentioned
above - that what is very important for the project development.
Apache HAWQ is a Hadoop native SQL query engine that combines the key
technological advantages of MPP database with the scalability and
convenience of Hadoop. HAWQ reads data from and writes data to HDFS
natively. HAWQ delivers industry-leading performance and linear
scalability. It provides users the tools to confidently and successfully
interact with petabyte range data sets. HAWQ provides users with a complete,
standards compliant SQL interface.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards graduation:
1. Produce our first Apache Release
2. Expand the community, increase dev list activity and adding new
contributors
3. Infrastructure migration: create Jenkins projects that build HAWQ
binary, source tarballs and docker images, and run feature tests
including at least installcheck-good tests for each commit (HAWQ-127).
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be
aware of?
Everything seems to be smooth, nothing urgent at this time.
How has the community developed since the last report?
1. All core contributors/committers have started working on Apache
repository
2. One HAWQ Nest community meeting (topic: HAWQ architecture introduction)
3. Both user & dev community show increasing interests. In Nov, there have
been 438 messages on dev@ and 75 on user@, compared with 357 messages
on dev@ and 21 messages on user@ in Oct.
How has the project developed since the last report?
1. Main features/improvements added include:
a) Support HA for libyarn [HAWQ-38]
b) Dynamic statement level resource usage [HAWQ-47]
c) Support Kerberos for libyarn [HAWQ-51]
d) Dependent component version upgrade & Bug fixes & documentation
improvement
2. First release has been proposed and most issues have been finished (115
issues resolved in the release). (<http://s.apache.org/T3P>)
Left thing is to do the PPMC & IPMC voting)
3. 85 new JIRAs filed, 74 resolved (In Nov 2015)
4. 76 code commits (In Nov 2015)
Date of last release:
We have not had a release yet.
When were the last committers or PMC members elected?
No new committers/members from initial.
Signed-off-by:
[X](hawq) Alan Gates
[X](hawq) Konstantin Boudnik
[ ](hawq) Justin Erenkrantz
[ ](hawq) Thejas Nair
[X](hawq) Roman Shaposhnik
Shepherd/Mentor notes:
HAWQ is an advanced enterprise SQL on Hadoop analytic engine built around a
robust and high-performance massively-parallel processing (MPP) SQL
framework evolved from Pivotal Greenplum Database.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards graduation:
1. Produce our first Apache Release
2. Expand the community, increase dev list activity and adding new
committers/pmc members
3. Infrastructure migration: create Jenkins projects that build HAWQ
binary, source tarballs and docker images, and run feature tests
including at least installcheck-good tests for each commit (HAWQ-127).
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be
aware of?
We have only just started the incubation, everything seems to be smooth,
nothing urgent at this time.
How has the community developed since the last report?
1. Most of the core contributors/committers have started working on Apache
repository
2. One Meetup for HAWQ hosted by "Big Data Community" in Beijing.
3. The community is active with the development of the project. In Oct,
There have been 357 messages on dev@. and 21 messages on user@,
compared with 95 messages in total last month.
4. Community shows interests to integrate HAWQ with systems in the
ecosystem.
How has the project developed since the last report?
1. First release has been proposed and targeted in Nov
(<http://s.apache.org/p4L6>)
2. 95 JIRAs filed, 46 open, 30 resolved, 19 closed (In Oct 2015)
3. 58 code commits (In Oct 2015)
Date of last release:
We have not had a release yet.
When were the last committers or PMC members elected?
No new committers/members from initial.
Signed-off-by:
[X](hawq) Alan Gates
[X](hawq) Konstantin Boudnik
[X](hawq) Justin Erenkrantz
[X](hawq) Thejas Nair
[X](hawq) Roman Shaposhnik
Shepherd/Mentor notes:
HAWQ is an advanced enterprise SQL on Hadoop analytic engine built around a
robust and high-performance massively-parallel processing (MPP) SQL framework
evolved from Pivotal Greenplum Database.
HAWQ has been incubating since 2015-09-04.
Three most important issues to address in the move towards graduation:
1. Produce our first Apache Release
2. Finalize infrastructure Migration and ICLAs from committers
3. Expand the community, increase dev list activity and adding new
committers/pmc members
Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be
aware of?
We have only just started the incubation, everything seems to be starting
up, nothing urgent at this time.
How has the community developed since the last report?
This is our first report, after having been approved for incubation roughly
2 wks ago.
1. Most of the core contributors have completed their ICLA's and have
established apache ids.
2. Several presentations and meetups at ApacheCon EU and Strata aimed at
growing interest in the project
3. Formal announcements from Pivotal and press briefings related to the
move of the project into Apache aimed at growing awareness and interest
in the project.
4. Outreach to parties that have expressed interest previously in our open
source initiatives
5. Still very much at the early stages of community development, we're just
starting to get rolling.
How has the project developed since the last report?
This is our first report, after having been approved for incubation roughly
2 wks ago.
1. Initial code drop has been provided to Apache
2. Core infrastructure has been setup including: mailing lists, git, jira,
wiki, website
3. 62 messages on our developer list, 3 messages on our user list
4. 16 jiras filed, 10 open, 1 reopened, 4 resolved, 1 closed - 1 issue
unassigned
5. 7 commits in total, including initial commit
6. Most discussed items on the mailing list:
- addressing issues with getting jira configured to allow issues to be
assigned to users
- discussion of usage of alternate communication channels, e.g. chat.
- discussion of RTC vs CTR models for dev process
Date of last release:
We have not had a release yet.
When were the last committers or PMC members elected?
Most of the initial list of committers have been onboarded, but there are
still a few more outstanding. We have not yet added any new members on top
of the initial committer list.
Signed-off-by:
[X](hawq) Alan Gates
[x](hawq) Konstantin Boudnik
[x](hawq) Justin Erenkrantz
[ ](hawq) Owen O'Malley
[ ](hawq) Thejas Nair
[ ](hawq) Roman Shaposhnik
Shepherd/Mentor notes: