Memcached 1.5.6 Release Notes

Memcached 1.5.6 Release Notes
Date: 2018-2-27


This is a bugfix release, but it primarily disables the UDP protocol by default.
In the last few days reports of UDP amplification attacks utilizing inesure
memcached instances have surfaced. Attackers are able to set large values into
memcached, then send requests via spoofed UDP packets. Memcached will then
send a very large number of very large UDP packets back in response.
12 years ago, the UDP version of the protocol had more widespread use: TCP
overhead could be very high. In the last few years, I’ve not heard of anyone
using UDP anymore. Proxies and special clients allow connection reuse, which
lowers the overhead. Also, RAM values are so large that TCP buffers just don’t
add up as much as they used to.
That said, I don’t have any way of knowing how many UDP installations there
are. Everyone who uses UDP and upgrades past this version, will find the UDP
protocol disabled unless they explicitly

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Queryparser, an Open Source Tool for Parsing and Analyzing SQL

In early 2015, Uber Engineering migrated its business entities from integer identifiers to UUID identifiers as part of an initiative towards using multiple active data centers. To achieve this, our Data Warehouse team was tasked with identifying every foreign-key relationship between every table in the data warehouse to backfill all the ID columns with corresponding UUIDs.¹
Given the decentralized ownership of our tables, this was not a simple endeavor. The most promising solution was to crowdsource the information by scraping all the SQL queries submitted to the warehouse and observing which columns were joined together. To serve this need, we built and open sourced Queryparser, our tool for parsing and analyzing SQL queries.
In this article, we discuss our implementation of Queryparser, the variety of applications it unlocked, and some problems and limitations encountered along the way.

Internally, Queryparser is deployed in a streaming architecture, as shown in Figure 1, below:
Figure 1: Uber’s

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Tensorflow 1.6.0 Released

Breaking Changes
Prebuilt binaries are now built against CUDA 9.0 and cuDNN 7.
Prebuilt binaries will use AVX instructions. This may break TF on older CPUs.
Major Features And Improvements
New Optimizer internal API for non-slot variables. Descendants of AdamOptimizer that access _beta[12]_power will need to be updated.
tf.estimator.{FinalExporter,LatestExporter} now export stripped SavedModels. This improves forward compatibility of the SavedModel.
FFT support added to XLA CPU/GPU.
Android TF can now be built with CUDA acceleration on compatible Tegra devices (see contrib/makefile/ for more information)
Bug Fixes and Other Changes
Documentation updates:
Added a second version of Getting Started, which is aimed at MLnewcomers.
Clarified documentation on resize_images.align_corners parameter.
Additional documentation for TPUs.

Google Cloud Storage (GCS):
Add client-side throttle.
Add a FlushCaches() method to the FileSystem interface, with an implementation for GcsFileSystem.

Add tf.contrib.distributions.Kumaraswamy.
RetryingFileSystem::FlushCaches() calls the base FileSystem’s FlushCaches().
Add auto_correlation to distributions.
Add tf.contrib.distributions.Autoregressive.
Add SeparableConv1D layer.
Add convolutional Flipout layers.
When both inputs of tf.matmul are bfloat16, it returns bfloat16, instead of float32.
Added tf.contrib.image.connected_components.
Add tf.contrib.framework.CriticalSection that allows atomic variable

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