MongoDB 3.2.10-rc2 is out and is ready for testing. This is a release candidate containing only fixes since 3.2.9. The next stable release 3.2.10 will be a recommended upgrade for all 3.2 users.
Fixed in this release:
- SERVER-12048 Calling "service mongod start" with mongod running prevents "service mongod stop" from working
- SERVER-16801 Update considers a change in numerical type to be a noop
- SERVER-24885 The systemd MaxTasks feature can prevent mongod from accepting new connections
- SERVER-24971 Excessive memory held by sessions when application threads do evictions
- SERVER-25478 Use wtimeout in sh.setBalancerState
- SERVER-25951 Report additional metrics in getMore slowms logging
- SERVER-25039 Aggregation can attempt to re-plan after collection has been dropped
- SERVER-25478 Use wtimeout in sh.setBalancerState
- TOOLS-1429 mongostat panic when monitored server is restarted
- WT-2026 Maximum pages size at eviction too large
- WT-2924 Ensure we are doing eviction when threads are waiting for it
As always, please let us know of any issues.
-- The MongoDB Team
How Saavn Grew to India’s Largest Music Streaming Service with MongoDB
Building a push notification system on a sophisticated data analytics pipeline powered by Apache Kafka, Storm and MongoDB 2015 was an important year for the music industry. It was the first time digital became the primary revenue source for recorded music, overtaking sales of physical formats. Key to this milestone was the revenue generated by streaming services – growing over 45% in a single year. As with many consumer services, the music streaming market is fragmented across the globe. In India – the 2nd most populous country on the planet and second largest smartphone market – Saavn has grown to become the sub-continent’s largest music service. It has 80m subscribers, experiencing a 9x increase in Daily Active Users (DAU) in just 24 months, with 90% of its streams served to mobile users. There are many factors that collectively have driven Saavn’s growth – but at the heart of it is data. And for this, they rely on MongoDB. !(https://webassets.mongodb.com/_com_assets/cms/Saavn-Logo-Horizontal-White-500-eua0kyb1uk.png) Saavn started out using MongoDB as a persistent cache, replacing an existing memcached layer. They soon realised the versatility and flexibility of the database to serve as the system of record for its data on subscribers, devices, and user activity. It was MongoDB’s flexibility and scalability that proved instrumental to maintain pace with Saavn’s breakneck growth. Through its extensive collection of music, the company quickly attracted new users to its streaming service, but found engagement often dropped away. It identified that push notifications sent directly to client devices was key to reconnecting with users, and keeping them engaged by serving personalized playlists. At this year’s MongoDB World conference, CTO Sriranjan Manjunath, presented how Saavn has used MongoDB as part of a sophisticated analytics pipeline to drive a 3x increase in user engagement. As Sriranjan and his team observed, it wasn’t enough to simply broadcast generic notifications to its users. Instead Saavn needed to craft notifications that provided playlists personalized to each user. Saavn built a sophisticated data processing pipeline that uses a scheduler to extract device, activity and user data stored in MongoDB. From there, it computes relevant playlists by analyzing a user’s listening preferences, activity, device, location and more. It then sends the computed recommendations to a dispatcher process that delivers the playlist to each user’s device and inbox. To refine personalizations, all user activity is ingested back into a Kafka queue where it is processed by Apache Storm and written back to MongoDB. Saavn is also expanding its use of artificial intelligence to better predict users interests, and is using MongoDB to store the resultant machine learning models and serve them in real time to the recommender application. The system currently sends 30m notifications per day, but has been sized to support up to 1m per minute, providing plenty of headroom to support Saavn’s continued growth. In his presentation, Sriranjan discussed how Saavn migrated from MongoDB 2.6 to MongoDB 3.0, taking advantage of the WiredTiger storage engine’s document level concurrency control to deliver improved performance. He talks about his key learnings in modifying schema design to reflect the differences in how updates are handled by the underlying storage engine, and usage of TTL indexes to automatically expire data from MongoDB . Sriranjan also discusses shard key selection to optimize uniform data distribution across the cluster, and the benefits of using MongoDB Cloud Manager for system monitoring and continuous backups, including integration with Slack for automated alerting to the ops team. Click through to view Saavn’s presentation from MongoDB World To learn more about managing real time streaming data, download: The MongoDB and Kafka white paper About the author - Mat Keep Mat is a director within the MongoDB product marketing team, responsible for building the vision, positioning and content for MongoDB’s products and services, including the analysis of market trends and customer requirements. Prior to MongoDB, Mat was director of product management at Oracle Corp. with responsibility for the MySQL database in web, telecoms, cloud and big data workloads. This followed a series of sales, business development and analyst / programmer positions with both technology vendors and end-user companies.
MongoDB at AWS re:Invent 2020
While 2020 has been a challenging year, it has also given rise to new levels of innovative collaboration and agile thinking. Where better to experience both than at AWS re:Invent 2020? At MongoDB, we’re excited to partner with AWS on this free, 3-week virtual event, providing unlimited access to hundreds of sessions led by Cloud experts. Although we’ll miss the grand, buzzing halls of the Venetian Hotel and the celebratory sounds of slot machines this year, it’s still important to approach AWS re:Invent with a focused plan. Think of this year’s event as an opportunity to curate your own perfectly tailored experience. Check out this page for details of our fresh new lineup of deep-dives, targeted jam sessions and — of course — the annual MongoDB late-night party. Here are some of the highlights. AWS Jam — "Excel isn't a database!" Imagine this: It's your first week in a new job, and the VP of sales has already given you an important data task. The good news? From the start of the year, all your current sales data has been stored in MongoDB Atlas — allowing operational and analytical workloads to run on the live data set. The not-so-good news? That wasn't always the case. For years before they switched, their database (well, ”database”) of choice was… Excel. Fortunately someone took the initiative to export that data in CSV format and store it in S3, but now the sales team needs your help to analyze that data — and they need it fast. In our “Excel isn’t a database!” Jam Session, you’ll test and upgrade your skills by connecting MongoDB Atlas Data Lake to CSV data that’s been languishing in an S3 bucket. Then you’ll run an aggregation to complete the challenge and claim points. Game on! This jam session will be available on-demand for the duration of AWS re:Invent Databases & S3: Auto-archiving Breakout Session Databases are built for fast access, but this can also make them resource-intensive. As data grows, you may want to optimize performance (or cost) by migrating old or infrequently used data into cheap object storage. But this presents its own problems: automating the archival process, ensuring data consistency during failures, and either querying two data stores separately or building a query federation system. In this talk, you’ll learn about how we approached these problems while building Online Archive and Federated Query features into MongoDB Atlas, lessons learned from the experience, and how you can do the same. MongoDB Late Nite That’s right: it’s a party! In the spirit of Vegas, MongoDB will be hosting an interactive late-night bash complete with throw-back entertainment at our virtual after-hours event. Like Vegas, there’s something for everyone. Unlike Vegas, the odds are actually on your side. Get your adrenaline going and dial in for exclusive swag at our Home Shopping Network. Just sign on and dial into our custom QVC-reboot every hour for a chance to snag some really cool limited-release items. Stay tuned to the event website to find out what you can win, and when! Are you a Jeopardy lover? MongoDB Late Nite is your time to shine. Exercise your mental reflexes and get those synapses firing with hundreds of other party people inside episodes of dev-focused live trivia. And what kind of revelry is complete without a resident psychic on board? Join us at the Future of Coding for an interactive reading by a VERY accurate psychic. So kick back, grab a beverage and join us at the party from home. Let’s get in the spirit together! Sponsor Page/Online Booth Pop into our virtual sponsor booth at your convenience. Our product experts will be there to answer your questions one-on-one. Alternatively, if casually exploring resources is more your style, check out our self-serve content playlists. View these to dig deeper into MongoDB education, glean customer success stories and get up to speed on the latest product features.