In online marketplaces, an increasing number of producers depend on search and recommendation systems to connect them with consumers to make a living. In this talk, we discuss how these systems will need to evolve from the traditional formulations by incorporating the producer value into their objectives. Jointly optimizing the ranking functions behind these systems on both consumer and producer values is a new direction and raises many technical challenges. To overcome these, we lay out an end-to-end solution and present the results of applying this solution on Facebook Marketplace.

Many applications demand availability. Unfortunately, software failures greatly reduce system availability. Prior work on surviving software failures suffers from one or more of the following limitations: required application restructuring, inability to address deterministic software bugs, unsafe speculation on program execution, and long recovery time. This paper proposes an innovative safe technique, called Rx, which can quickly recover programs from many types of software bugs, both deterministic and nondeterministic. Our idea, inspired from allergy treatment in real life, is to rollback the program to a recent checkpoint upon a software failure, and then to reexecute the program in a modified environment. We base this idea on the observation that many bugs are correlated with the execution environment, and therefore can be avoided by removing the “allergen” from the environment. Rx requires few to no modifications to applications and provides programmers with additional feedback for bug diagnosis. We have implemented Rx on Linux. Our experiments with five server applications that contain seven bugs of various types show that Rx can survive six out of seven software failures and provide transparent fast recovery within 0.017--0.16 seconds, 21--53 times faster than the whole program restart approach for all but one case (CVS). In contrast, the two tested alternatives, a whole program restart approach and a simple rollback and reexecution without environmental changes, cannot successfully recover the four servers (Squid, Apache, CVS, and ypserv) that contain deterministic bugs, and have only a 40% recovery rate for the server (MySQL) that contains a nondeterministic concurrency bug. Additionally, Rx's checkpointing system is lightweight, imposing small time and space overheads.

Many applications demand availability. Unfortunately, software failures greatly reduce system availability. Prior work on surviving software failures suffers from one or more of the following limitations: Required application restructuring, inability to address deterministic software bugs, unsafe speculation on program execution, and long recovery time.This paper proposes an innovative safe technique, called Rx, which can quickly recover programs from many types of software bugs, both deterministic and non-deterministic. Our idea, inspired from allergy treatment in real life, is to rollback the program to a recent checkpoint upon a software failure, and then to re-execute the program in a modified environment. We base this idea on the observation that many bugs are correlated with the execution environment, and therefore can be avoided by removing the "allergen" from the environment. Rx requires few to no modifications to applications and provides programmers with additional feedback for bug diagnosis.We have implemented RX on Linux. Our experiments with four server applications that contain six bugs of various types show that RX can survive all the six software failures and provide transparent fast recovery within 0.017-0.16 seconds, 21-53 times faster than the whole program restart approach for all but one case (CVS). In contrast, the two tested alternatives, a whole program restart approach and a simple rollback and re-execution without environmental changes, cannot successfully recover the three servers (Squid, Apache, and CVS) that contain deterministic bugs, and have only a 40% recovery rate for the server (MySQL) that contains a non-deterministic concurrency bug. Additionally, RX's checkpointing system is lightweight, imposing small time and space overheads.

Memory can be efficiently utilized if the dynamic memory demands of applications can be determined and analyzed at run-time. The page miss ratio curve(MRC), i.e. page miss rate vs. memory size curve, is a good performance-directed metric to serve this purpose. However, dynamically tracking MRC at run time is challenging in systems with virtual memory because not every memory reference passes through the operating system (OS).This paper proposes two methods to dynamically track MRC of applications at run time. The first method is using a hardware MRC monitor that can track MRC at fine time granularity. Our simulation results show that this monitor has negligible performance and energy overheads. The second method is an OS-only implementation that can track MRC at coarse time granularity. Our implementation results on Linux show that it adds only 7--10% overhead.We have also used the dynamic MRC to guide both memory allocation for multiprogramming systems and memory energy management. Our real system experiments on Linux with applications including Apache Web Server show that the MRC-directed memory allocation can speed up the applications' execution/response time by up to a factor of 5.86 and reduce the number of page faults by up to 63.1%. Our execution-driven simulation results with SPEC2000 benchmarks show that the MRC-directed memory energy management can improve the Energy * Delay metric by 27--58% over previously proposed static and dynamic schemes.