This document discusses GMO Internet's data analytics system for analyzing social game data from over 500 game titles across multiple data centers in Japan and the US. It summarizes the system's architecture, which uses Hadoop/Hive to process logging data from game servers into hourly, daily, weekly, and monthly reports on key performance indicators. The system partitions and stores large volumes of data across multiple NameNodes and processes over 6 million blocks and 44,000 jobs per day to generate conversion counts and other analytics for A/B testing.
Scio - Moving to Google Cloud, A Spotify StoryNeville Li
Talk at Philly ETE Apr 28 2017
We will talk about Spotify’s story of migrating our big data infrastructure to Google Cloud. Over the past year or so we moved away from maintaining our own 2500+ node Hadoop cluster to managed services in the cloud. We replaced two key components in our data processing stack, Hive and Scalding, with BigQuery and Scio and are able to iterate at a much faster speed. We will focus the technical aspect of Scio, a Scala API for Apache Beam and Google Cloud Dataflow and how it changed the way we process data.
Sorry - How Bieber broke Google Cloud at SpotifyNeville Li
Talk at Scala Up North Jul 21 2017
We will talk about Spotify's story with Scala big data and our journey to migrate our entire data infrastructure to Google Cloud and how Justin Bieber contributed to breaking it. We'll talk about Scio, a Scala API for Apache Beam and Google Cloud Dataflow, and the technology behind it, including macros, algebird, chill and shapeless. There'll also be a live coding demo.
Beautiful Monitoring With Grafana and InfluxDBleesjensen
Query your data streams with the time series database InfluxDB and then visualize the results with stunning Grafana dashboards. Quick and easy to set up. Fully scalable to millions of metrics per second.
Scio - Moving to Google Cloud, A Spotify StoryNeville Li
Talk at Philly ETE Apr 28 2017
We will talk about Spotify’s story of migrating our big data infrastructure to Google Cloud. Over the past year or so we moved away from maintaining our own 2500+ node Hadoop cluster to managed services in the cloud. We replaced two key components in our data processing stack, Hive and Scalding, with BigQuery and Scio and are able to iterate at a much faster speed. We will focus the technical aspect of Scio, a Scala API for Apache Beam and Google Cloud Dataflow and how it changed the way we process data.
Sorry - How Bieber broke Google Cloud at SpotifyNeville Li
Talk at Scala Up North Jul 21 2017
We will talk about Spotify's story with Scala big data and our journey to migrate our entire data infrastructure to Google Cloud and how Justin Bieber contributed to breaking it. We'll talk about Scio, a Scala API for Apache Beam and Google Cloud Dataflow, and the technology behind it, including macros, algebird, chill and shapeless. There'll also be a live coding demo.
Beautiful Monitoring With Grafana and InfluxDBleesjensen
Query your data streams with the time series database InfluxDB and then visualize the results with stunning Grafana dashboards. Quick and easy to set up. Fully scalable to millions of metrics per second.
This presentation was inspired post read of "TimeSeries Databases" -- Ted Dunning & Ellen Friedman.
I have tried to summarize a lot of the previous bench marks. Hope others find it useful. The slides were compiled early 2015 so some of the results might have changed but the core literature should still hold.
Paul Dix (Founder InfluxDB) - Organising Metrics at #DOXLONOutlyer
Video:
Paul Dix (Founder of InfluxDB) talking about his awesome Open-Source projects for monitoring.
For more info visit: InfluxDB: www.influxdb.com
Join DevOps Exchange London here: http://www.meetup.com/DevOps-Exchange-London/
Follow DOXLON on twitter: twitter.com/doxlon
Over the past year data at GumGum has quadrupled. Now a days we process 20 TB of new data every day. New data/reporting requirements pour in every week. Usage of the real time data is growing with the daily data. In this talk we are tying to answer the following questions: How do we serve real time data with daily batched data to our consumers together? What is Lambda Architecture and how does it help? What role does Cassandra play in Lambda Architecture at GumGum? How did we solve few bottlenecks in the architecture using Cassandra? How Cassandra can help you avoid microbatching and give you a true realtime data?
About the Speaker
Vaibhav Puranik VP of Engineering, Big Data & Platform, GumGum
Vaibhav has 15 years of experience in Software. He began his career with Johnson Space Center in Houston and has a masters degree in computer science. For past 5 years Vaibhav has been responsible for architecting multiple big data systems at GumGum. He manages Data Science, Data Engineering and DevOps teams at GumGum.
Building real time analytics applications using pinot : A LinkedIn case studyKishore Gopalakrishna
LinkedIn's is the most advantageous social networking tool available to job seekers and business professionals today, with 610+ million members creating millions of posts, videos, and articles that generate tens of millions of shares, comments, and likes per day. LinkedIn has leveraged this activity data to build rich interactive user-facing analytics applications like “Who Viewed My Profile”, Talent Insights, Ad Analytics, and Publisher Analytics, among others. These applications are all powered by Pinot, as are internal dashboards, anomaly detection and root cause analysis platform like ThirdEye. This talk will present how Pinot has become the de-facto solution for serving analytic queries in milliseconds, ad-hoc reporting, monitoring & Anomaly Detection on multidimensional data.
InfluxDB 1.0 - Optimizing InfluxDB by Sam DillardInfluxData
Learn how to optimize InfluxDB 1.0 for performance including hardware and architecture choices, schema design, configuration setup, and running queries. In this InfluxDays NYC 2019 presentation, Sam Dillard provides numerous actionable tips and insights into InfluxDB optimization.
Server side geo_tools_in_drupal_pnw_2012Mack Hardy
Mack Hardy @mackaffinity from Affinity Bridge @affinitybridge discusses server side mapping tools for drupal, using PostGIS as a spatial backend, generating tiles and managing large sets of geodata and displaying it in Drupal CMS
This presentation was inspired post read of "TimeSeries Databases" -- Ted Dunning & Ellen Friedman.
I have tried to summarize a lot of the previous bench marks. Hope others find it useful. The slides were compiled early 2015 so some of the results might have changed but the core literature should still hold.
Paul Dix (Founder InfluxDB) - Organising Metrics at #DOXLONOutlyer
Video:
Paul Dix (Founder of InfluxDB) talking about his awesome Open-Source projects for monitoring.
For more info visit: InfluxDB: www.influxdb.com
Join DevOps Exchange London here: http://www.meetup.com/DevOps-Exchange-London/
Follow DOXLON on twitter: twitter.com/doxlon
Over the past year data at GumGum has quadrupled. Now a days we process 20 TB of new data every day. New data/reporting requirements pour in every week. Usage of the real time data is growing with the daily data. In this talk we are tying to answer the following questions: How do we serve real time data with daily batched data to our consumers together? What is Lambda Architecture and how does it help? What role does Cassandra play in Lambda Architecture at GumGum? How did we solve few bottlenecks in the architecture using Cassandra? How Cassandra can help you avoid microbatching and give you a true realtime data?
About the Speaker
Vaibhav Puranik VP of Engineering, Big Data & Platform, GumGum
Vaibhav has 15 years of experience in Software. He began his career with Johnson Space Center in Houston and has a masters degree in computer science. For past 5 years Vaibhav has been responsible for architecting multiple big data systems at GumGum. He manages Data Science, Data Engineering and DevOps teams at GumGum.
Building real time analytics applications using pinot : A LinkedIn case studyKishore Gopalakrishna
LinkedIn's is the most advantageous social networking tool available to job seekers and business professionals today, with 610+ million members creating millions of posts, videos, and articles that generate tens of millions of shares, comments, and likes per day. LinkedIn has leveraged this activity data to build rich interactive user-facing analytics applications like “Who Viewed My Profile”, Talent Insights, Ad Analytics, and Publisher Analytics, among others. These applications are all powered by Pinot, as are internal dashboards, anomaly detection and root cause analysis platform like ThirdEye. This talk will present how Pinot has become the de-facto solution for serving analytic queries in milliseconds, ad-hoc reporting, monitoring & Anomaly Detection on multidimensional data.
InfluxDB 1.0 - Optimizing InfluxDB by Sam DillardInfluxData
Learn how to optimize InfluxDB 1.0 for performance including hardware and architecture choices, schema design, configuration setup, and running queries. In this InfluxDays NYC 2019 presentation, Sam Dillard provides numerous actionable tips and insights into InfluxDB optimization.
Server side geo_tools_in_drupal_pnw_2012Mack Hardy
Mack Hardy @mackaffinity from Affinity Bridge @affinitybridge discusses server side mapping tools for drupal, using PostGIS as a spatial backend, generating tiles and managing large sets of geodata and displaying it in Drupal CMS
Hadoop YARN is the next generation computing platform in Apache Hadoop with support for programming paradigms besides MapReduce. In the world of Big Data, one cannot solve all the problems wholly using the Map Reduce programming model. Typical installations run separate programming models like MR, MPI, graph-processing frameworks on individual clusters. Running fewer larger clusters is cheaper than running more small clusters. Therefore,_leveraging YARN to allow both MR and non-MR applications to run on top of a common cluster becomes more important from an economical and operational point of view. This talk will cover the different APIs and RPC protocols that are available for developers to implement new application frameworks on top of YARN. We will also go through a simple application which demonstrates how one can implement their own Application Master, schedule requests to the YARN resource-manager and then subsequently use the allocated resources to run user code on the NodeManagers.
Application Monitoring using Open Source: VictoriaMetrics - ClickHouseVictoriaMetrics
Monitoring is the key to successful operation of any software service, but commercial solutions are complex, expensive, and slow. Let us show you how to build monitoring that is simple, cost-effective, and fast using open source stacks easily accessible to any developer.
We’ll start with the elements of monitoring systems: data ingest, query engine, visualization, and alerting. We’ll then explain and contrast two implementation approaches. The first uses VictoriaMetrics, a fast growing, high performance time series database that uses PromQL for queries. The second is based on ClickHouse, a popular real-time analytics database that speaks SQL. Fast, affordable monitoring is within reach. This webinar provides designs and working code to get you there.
Application Monitoring using Open Source - VictoriaMetrics & Altinity ClickHo...Altinity Ltd
Application Monitoring using Open Source - VictoriaMetrics & Altinity ClickHouse Webinar Slides
Monitoring is the key to the successful operation of any software service, but commercial solutions are complex, expensive, and slow. Let us show you how to build monitoring that is simple, cost-effective, and fast using open-source stacks easily accessible to any developer.
We’ll start with the elements of monitoring systems: data ingest, query engine, visualization, and alerting. We’ll then explain and contrast two implementation approaches. The first uses VictoriaMetrics, a fast-growing, high-performance time series database that uses PromQL for queries. The second is based on ClickHouse, a popular real-time analytics database that speaks SQL. Fast, affordable monitoring is within reach. This webinar provides designs and working code to get you there.
Presented by:
Roman Khavronenko, Co-Founder at VictoriaMetrics
Robert Hodges, CEO at Altinity
Sergei Sokolenko "Advances in Stream Analytics: Apache Beam and Google Cloud ...Fwdays
In this session, Sergei Sokolenko, the Google product manager for Cloud Dataflow, will share the implementation details of many of the unique features available in Apache Beam and Cloud Dataflow, including:
- autoscaling of resources based on data inputs;
- separating compute and state storage for better scaling of resources;
- simultaneous grouping and joining of 100s of Terabytes in a hybrid in-memory/on-desk file system;
- dynamic work rebalancing of work items away from overutilized worker nodes and many others.
Customers benefit from these advances through faster execution of jobs, resource savings, and a fully managed data processing environment that runs in the Cloud and removes the need to manage infrastructure.
WSO2Con ASIA 2016: WSO2 Analytics Platform: The One Stop Shop for All Your Da...WSO2
Today’s highly connected world is flooding businesses with big and fast-moving data. The ability to trawl this data ocean and identify actionable insights can deliver a competitive advantage to any organization. The WSO2 Analytics Platform enables businesses to do just that by providing batch, real-time, interactive and predictive analysis capabilities all in one place.
In this tutorial we will
Plug in the WSO2 Analytics Platform to some common business use cases
Showcase the numerous capabilities of the platform
Demonstrate how to collect data, analyze, predict and communicate effectively
Building a Real-Time Gaming Analytics Service with Apache DruidImply
At GameAnalytics we receive and process real time behavioural data from more than 100 million daily active users, helping thousands of game studios and developers understand user behaviour and improve their games. In this talk, you will learn how we managed to migrate our legacy backend system from using an in-house built streaming analytics service to Apache Druid, and the lessons learned along the way. By adopting Druid, we have been able to reduce development costs, increase reliability of our systems and implement new features that would have not been possible with our old stack. We will provide an overview of our approach to schema design, segments optimization, creation of our query layer, caching and datasources optimisation, which can help you better understand how you can successfully use Druid as a key component on your data processing and reporting infrastructure.
Transforming Mobile Push Notifications with Big Dataplumbee
How we at Plumbee collect and process data at scale and how this data is used to send relevant mobile push notifications to our players to keep them engaged.
Presented as part of a Tech Talk: http://engineering.plumbee.com/blog/2014/11/07/tech-talk-push-notifications-big-data/
So, you have IoT Devices connected to IoT Hub sending telemetry data into the Microsoft Azure cloud. Now what? This session will take you through setting up real-time stream processing of IoT data. We’ll look at integrating services like Azure Stream Analytics, Azure Functions, and Cosmos DB to build a highly scalable stream processing backend for any IoT solution. You’ll leave this session better prepared to handle real-time IoT stream processing in Azure; plus you’ll do it with less code by utilizing serverless Azure Functions.
Strata Presentation: One Billion Objects in 2GB: Big Data Analytics on Small ...randyguck
Slides from my Strata+Hadoop 2015 Conference session titled: One Billion Objects in 2GB: Big Data Analytics on Small Clusters with Doradus OLAP. This talk describes the Doradus OLAP query/storage engine, which is an open source module that runs on top of the Cassandra NoSQL DB. Among the benefits of this service is fast data loading, a rich query language with full text and graph query features, and very dense data storage. See the Notes section for details on each slide.
WSO2Con USA 2015: WSO2 Analytics Platform - The One Stop Shop for All Your Da...WSO2
Today’s highly connected world is flooding businesses with big and fast-moving data. The ability to trawl this data ocean and identify actionable insights can deliver a competitive advantage to any organization. The WSO2 Analytics Platform enables businesses to do just that by providing batch, real-time, interactive and predictive analysis capabilities all in one place.
If you are building a service oriented system and you want to build it for scale as well as flexibility. There are a few questions you need to make sure are asked and answered regarding the data interchange between services and offline persistency of services data. Questions as:
- How can I change a service API without breaking other services?
- How do I keep data from services consistent over time?
This talk covers the challenges we tackled during building our new service oriented system. Summarizing what we realized would bad Ideas to do, what are the better approaches to data consistency.
It includes a dive into the Apache Avro technology and how we used it.
Also what other supporting infrastructure we created to help us achieving the goal of consistent yet flexible system.
This slide deck explores WSO2 Stream Processor’s new features and improvements and explain how they make an organization excel in the current competitive marketplace.
This session takes an in-depth look at:
- Trends in stream processing
- How streaming SQL has become a standard
- The advantages of Streaming SQL
- Ease of development with streaming SQL: Graphical and Streaming SQL query editors
- Business value of streaming SQL and its related tools: Domain-specific UIs
- Scalable deployment of streaming SQL: Distributed processing
Similar to Data analytics with hadoop hive on multiple data centers (20)
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
3. Data Analytics System
●
KPI reporting system for Cloud System
●
GMO Apps Cloud
●
Over 500 Titles
mobage, gree, mixi, Hangame, facebook, nikoniko … etc
●
Data Center
Japan, US(west coast)
4. Analytics Specification
●
Social Game Data KPI
DAU/PV, Play Time, Sales
A/B Testing, Conversion … etc
●
Hourly, Daily, Weekly, Monthly
●
Since 2010/06 ~
5. System Architecture
SNS Game
User SNS Platform Master
Cloud System Management Monitoring
System System
Cloud Server
(Game Server)
Logging
Scheduler ・・・・・・・・
Server
MySQL
Hadoop/Hive
(for Hive)
Data Center A Data Center N
6. Specification, Statistics
●
Multiple NameNode per Data Center
●
Hardware Spacification
CPU : 8~16CPU(HT)
MEM: 12~64Gbyte
HD : RAID 1, 5, 1+0
●
Statistics
6,000,000 blocks/44,000 jobs/day
1,000 over AP servers logging
7. Data Flow
load data local inpath 'hogehoge-access_log.*.log.gz'
overwrite into table original_logs
partition (log_date='2012-07-26', log_number=13);
host string from deserializer
identity string from deserializer
user string from deserializer Cloud Server
time string from deserializer (Game Server)
method string from deserializer
request string from deserializer
status string from deserializer Logging
size string from deserializer Management
Server System
referer string from deserializer
agent string from deserializer
log_date string
log_number tinyint
Hadoop/Hive Scheduler
host string
time string
method string HiveDriver
request string
userid string
log_date string Filter → Hourly, Daily, Weekly, Monthly Report
log_number tinyint (AB Testing, Conversion, DAU..etc)
8. Conversion Count HQL
INSERT OVERWRITE TABLE conversion_click
PARTITION (log_date= :logDate, log_number=:logNumber)
SELECT regexp_extract(request, 'convid=([a-zA-Z0-9%])', 1),
regexp_extract(request, 'convflg=(A|B){1}', 1),
count(1),
:logMonth,
:logWeek
FROM parsed_log
WHERE request RLIKE 'convid=[a-zA-Z0-9%]'
AND request RLIKE 'convflg=(A|B){1}'
AND log_date = :logDate
AND log_number = :logNumber
GROUP BY regexp_extract(request, 'convid=([a-zA-Z0-9%])', 1),
regexp_extract(request, 'convflg=(A|B){1}', 1)