After upgrading an Oracle database from version 18.7 to 19.12, queries began encountering errors such as ORA-07445 and ORA-00600, causing instance crashes. The errors seemed related to parsing and transformation components in the SQL processing pipeline. Adding more physical memory resolved the issue, indicating the new database version required more memory than the previous configuration.
Use dependency injection to get Hadoop *out* of your application codeDataWorks Summit
Hadoop MapReduce provides transparent parallelization but often results in specialized code bases that interact with low-level data formats. We present a means of using dependency injection to manage data flows in MapReduce which in turn supports reusable, Hadoop-agnostic application code that interacts with high-level business domain objects. An example is provided that applies Dependency Injection to the Hadoop WordCount example and shows how the same code invoked from the WordCount MapReduce job can be reused in a real-time context. We then discuss Opower’s application of this pattern to employ the same core calculations in both batch processing and in servicing real-time requests from end users. This topic will be of interest to those interested in reusing core batch calculations in real-time contexts. It also provides a means forward for organizations moving to Hadoop that have existing code components that they would like to employ in batch MapReduce computations.
These slides are from the recent meetup @ Uber - Apache Cassandra at Uber and Netflix on new features in 4.0.
Abstract:
A glimpse of Cassandra 4.0 features:
There are a lot of exciting features coming in 4.0, but this talk covers some of the features that we at Netflix are particularly excited about and looking forward to. In this talk, we present an overview of just some of the many improvements shipping soon in 4.0.
Use dependency injection to get Hadoop *out* of your application codeDataWorks Summit
Hadoop MapReduce provides transparent parallelization but often results in specialized code bases that interact with low-level data formats. We present a means of using dependency injection to manage data flows in MapReduce which in turn supports reusable, Hadoop-agnostic application code that interacts with high-level business domain objects. An example is provided that applies Dependency Injection to the Hadoop WordCount example and shows how the same code invoked from the WordCount MapReduce job can be reused in a real-time context. We then discuss Opower’s application of this pattern to employ the same core calculations in both batch processing and in servicing real-time requests from end users. This topic will be of interest to those interested in reusing core batch calculations in real-time contexts. It also provides a means forward for organizations moving to Hadoop that have existing code components that they would like to employ in batch MapReduce computations.
These slides are from the recent meetup @ Uber - Apache Cassandra at Uber and Netflix on new features in 4.0.
Abstract:
A glimpse of Cassandra 4.0 features:
There are a lot of exciting features coming in 4.0, but this talk covers some of the features that we at Netflix are particularly excited about and looking forward to. In this talk, we present an overview of just some of the many improvements shipping soon in 4.0.
Optimizing Oracle Databases & Applications Gives Fast Food Giant Major GainsDatavail
A leader in the fast-food industry began experiencing issues with database performance and financial close processes that were having major effects on the business. By implementing optimization techniques, re-architecting systems, migrating to the cloud, and properly distributing server load, this fast-food giant was able to:
Cut server lag from 24 hours to five minutes during even the most active periods
Decrease time to implement global changes to menus from one week to overnight
Speed their financial close time frame
Significantly reduce the frequency of crashes and downtime
And more!
Watch this webinar to learn HOW this was achieved with our 5S performance tuning methodology, so you can do the same in your own environment.
Oracle Database features every developer should know aboutgvenzl
This presentation highlights some Oracle Database features that make developers more productive when using Oracle Database. The slide deck does only contain a sample of many useful developer features inside the Oracle Database. Developers should always refer to the Oracle Database Development Guide (https://docs.oracle.com/en/database/oracle/oracle-database/18/adfns/index.html)
This slide deck what co-produced with https://twitter.com/sqlmaria
Part 4 - Hadoop Data Output and Reporting using OBIEE11gMark Rittman
Delivered as a one-day seminar at the SIOUG and HROUG Oracle User Group Conferences, October 2014.
Once insights and analysis have been produced within your Hadoop cluster by analysts and technical staff, it’s usually the case that you want to share the output with a wider audience in the organisation. Oracle Business Intelligence has connectivity to Hadoop through Apache Hive compatibility, and other Oracle tools such as Oracle Big Data Discovery and Big Data SQL can be used to visualise and publish Hadoop data. In this final session we’ll look at what’s involved in connecting these tools to your Hadoop environment, and also consider where data is optimally located when large amounts of Hadoop data need to be analysed alongside more traditional data warehouse datasets
MySQL 8.0 is the latest Generally Available version of MySQL. Discover the new Document Store, using SQL and NoSQL (js, python, CRUD, etc.) with the same database, Data Dictionary, Invisible Indexes, the new default UTF8MB4 charset (for emojis), Windows Functions, Common Table Expressions, and so much more.
Optimizing Oracle Databases & Applications Gives Fast Food Giant Major GainsDatavail
A leader in the fast-food industry began experiencing issues with database performance and financial close processes that were having major effects on the business. By implementing optimization techniques, re-architecting systems, migrating to the cloud, and properly distributing server load, this fast-food giant was able to:
Cut server lag from 24 hours to five minutes during even the most active periods
Decrease time to implement global changes to menus from one week to overnight
Speed their financial close time frame
Significantly reduce the frequency of crashes and downtime
And more!
Watch this webinar to learn HOW this was achieved with our 5S performance tuning methodology, so you can do the same in your own environment.
Oracle Database features every developer should know aboutgvenzl
This presentation highlights some Oracle Database features that make developers more productive when using Oracle Database. The slide deck does only contain a sample of many useful developer features inside the Oracle Database. Developers should always refer to the Oracle Database Development Guide (https://docs.oracle.com/en/database/oracle/oracle-database/18/adfns/index.html)
This slide deck what co-produced with https://twitter.com/sqlmaria
Part 4 - Hadoop Data Output and Reporting using OBIEE11gMark Rittman
Delivered as a one-day seminar at the SIOUG and HROUG Oracle User Group Conferences, October 2014.
Once insights and analysis have been produced within your Hadoop cluster by analysts and technical staff, it’s usually the case that you want to share the output with a wider audience in the organisation. Oracle Business Intelligence has connectivity to Hadoop through Apache Hive compatibility, and other Oracle tools such as Oracle Big Data Discovery and Big Data SQL can be used to visualise and publish Hadoop data. In this final session we’ll look at what’s involved in connecting these tools to your Hadoop environment, and also consider where data is optimally located when large amounts of Hadoop data need to be analysed alongside more traditional data warehouse datasets
MySQL 8.0 is the latest Generally Available version of MySQL. Discover the new Document Store, using SQL and NoSQL (js, python, CRUD, etc.) with the same database, Data Dictionary, Invisible Indexes, the new default UTF8MB4 charset (for emojis), Windows Functions, Common Table Expressions, and so much more.
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
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We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
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From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
1. After upgrade oracle database from 18.7 to 19.12 we faced issues for our quires. For example below
errors occurred for some of quires:
ORA-07445: exception encountered: core dump [qcsabe_worker()+6] [SIGSEGV]
[ADDR:0x7FFF0CF89FF8] [PC:0x12DD87D6] [Address not mapped to object] []
ORA-07445: exception encountered: core dump [kkqojeanl()+836] [SIGSEGV]
[ADDR:0x7FFEFB4E5FB8] [PC:0x12C09734] [Address not mapped to object] []
Another error that caused instance crash was:
ORA-00600 [99999]
Queries that used of large inlists encountered the ora-07445 error. In general in oracle maximum
number of expressions in a list is 1000. If a program needs more than this should use of OR switch to
join inlists. By this method we can have inlist queries with 20000 or more item in our inlist.
Arguments in the ORA-07445
qcsabe: semantic analysis
kkqojeanl: expression analyze
It seems the errors relates to Parsing and Transformation components . Below tree shows that our
problem occurred in SQL Transformation component:
SQL_Compiler
→ SQL_Parser (qcs)
→SQL_Semantic
→SQL_Optimizer
→SQL_Transform (kkq)
Solutions:
1. Based on oracle docid 1577011.1 we should replace our large inlists with temporary table. But
this solution for us is not possible because these are SAP standard transactions.
2. Disable oracle transformation features by change below parameters:
_optimizer_cost_based_transformation
_optimizer_free_transformation_heap
_optimizer_use_cbqt_star_transformation
2. _optimizer_vector_transformation
But this doesn’t resolve our problem.
3. Probing the ora-00600 error and it shows us there is a problem in Oracle Resource Management
layer. It means Resource Management caused to crash the database. Of course we didn’t used
this feature at all. By checking trace files related to DB crash we guessed our problem relates to
lake of Physical Memory (RAM) and by adding Memory our problem has been solved. It means
the configuration that worked in 18.7 in 19.12 needs more memory.
1
.
![After upgrade oracle database from 18.7 to 19.12 we faced issues for our quires. For example below
errors occurred for some of quires:
ORA-07445: exception encountered: core dump [qcsabe_worker()+6] [SIGSEGV]
[ADDR:0x7FFF0CF89FF8] [PC:0x12DD87D6] [Address not mapped to object] []
ORA-07445: exception encountered: core dump [kkqojeanl()+836] [SIGSEGV]
[ADDR:0x7FFEFB4E5FB8] [PC:0x12C09734] [Address not mapped to object] []
Another error that caused instance crash was:
ORA-00600 [99999]
Queries that used of large inlists encountered the ora-07445 error. In general in oracle maximum
number of expressions in a list is 1000. If a program needs more than this should use of OR switch to
join inlists. By this method we can have inlist queries with 20000 or more item in our inlist.
Arguments in the ORA-07445
qcsabe: semantic analysis
kkqojeanl: expression analyze
It seems the errors relates to Parsing and Transformation components . Below tree shows that our
problem occurred in SQL Transformation component:
SQL_Compiler
→ SQL_Parser (qcs)
→SQL_Semantic
→SQL_Optimizer
→SQL_Transform (kkq)
Solutions:
1. Based on oracle docid 1577011.1 we should replace our large inlists with temporary table. But
this solution for us is not possible because these are SAP standard transactions.
2. Disable oracle transformation features by change below parameters:
_optimizer_cost_based_transformation
_optimizer_free_transformation_heap
_optimizer_use_cbqt_star_transformation](https://image.slidesharecdn.com/problemdetails-211005171729/85/Problem-details-1-320.jpg)
