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@toricls
toricls / lima-on-m1-mac-installation-guide.md
Last active November 9, 2024 23:03
Using Lima to run containers with containerd and nerdctl (without Docker Desktop) on M1 Macs

Lima (Linux virtual machines, on macOS) installation guide for M1 Mac.

Sep. 27th 2021 UPDATED

Now we can install patched version of QEMU via Homebrew (thank you everyone for the info!). Here is the updated instruction with it:

Used M1 Mac mini 2020 with macOS Big Sur Version 11.6.

1. Install QEMU & Lima

@adrian-baker
adrian-baker / AWSCredentialsProvider.java
Created October 6, 2018 21:39
Workaround https://github.com/aws/aws-sdk-java/issues/803
public AWSCredentialsProvider getDefaultCredentials() {
final String profileName = AwsProfileNameLoader.INSTANCE.loadProfileName();
final AllProfiles allProfiles = new AllProfiles(Stream.concat(
BasicProfileConfigLoader.INSTANCE.loadProfiles(
AwsProfileFileLocationProvider.DEFAULT_CONFIG_LOCATION_PROVIDER.getLocation()).getProfiles().values().stream(),
BasicProfileConfigLoader.INSTANCE.loadProfiles(
AwsProfileFileLocationProvider.DEFAULT_CREDENTIALS_LOCATION_PROVIDER.getLocation()).getProfiles().values().stream())
.map(profile -> new BasicProfile(profile.getProfileName().replaceFirst("^profile ", ""), profile.getProperties()))
.collect(Collectors.toMap(profile -> profile.getProfileName(), profile -> profile,
@frsyuki
frsyuki / Digdag task scan improvements.md
Last active October 1, 2020 04:30

Performance degradation due to too many active tasks

When we ran a stress testing tool on Digdag server, the server stopped running tasks. The cause was that propagateAllPlannedToDone and propagateBlockedChildrenToReady methods of io.digdag.core.workflow.WorkflowExecutor class were too slow when there're too many active tasks.

Here is the scenario:

  1. Many workflows submit many tasks.

  2. Eventually, there're a lot of tasks in PLANNED or BLOCKED tasks.

@gakuzzzz
gakuzzzz / sbt-coursier.md
Last active June 27, 2019 03:23
あなたの sbt update を爆速にする sbt-coursier の紹介

あなたの sbt update を爆速にする sbt-coursier の紹介

この記事は Scala Advent Calendar 2016(Adventar) 10日目の記事です。

今は 12/10 の 625時です。年明けなんて無かった。いいね？

さてさて、sbt の依存jarのダウンロードが遅い、というのは割とよく言われる事であります。

で、この原因の一旦に、sbtが Apache Ivy を使っている、という点があります。

@hiroyuki-sato
hiroyuki-sato / gist:aedcf2f195cee89adb3a
Last active August 29, 2015 14:25
embulk-output-hdfs rebult
git clone https://github.com/civitaspo/embulk-output-hdfs.git
cd embulk-output-hdfs
./gradlew gem
cd pkg
embulk gem install -l embulk-output-hdfs-0.1.0.gem
@gakuzzzz
gakuzzzz / file.md
Last active June 23, 2019 13:51
UserId など値型はどうするべきか

UserId などの型はどうするべきか

1. primitive 型をそのまま使う

case class Person(id: Long, name: String, organizationId: Long)
object Person {

  def groupByOrg: Map[Long, Seq[Person]] = ...
@svrc-personal
svrc-personal / gist:5a8accc57219b9548fe1
Last active May 11, 2020 15:39
JDK 8 seems to use /dev/urandom and /dev/random more sensibly
Summary of Behaviour:
A. OpenJDK 7 b65.
1. Default in java.security is securerandom.source=/dev/urandom
2. If securerandom.source=/dev/urandom, NativePRNG is used, SecureRandom.nextBytes() is non-blocking via /dev/urandom ; SecureRandom.generateSeed(x) is blocking via /dev/random
3. if securerandom.source=/dev/random, then SHA1PRNG is used. Initial seed is blocking via /dev/random. No other accesses.
4. If securerandom.source=/dev/./urandom then SHA1PRNG is used. Initial seed is non-blocking via /dev/./urandom. No other accesses.
B. Oracle JDK 8 b25.
@ueshin
ueshin / scalamatsuri2014.md
Created September 6, 2014 02:42
SparkSQL samples for ScalaMatsuri2014
@hofmannsven
hofmannsven / README.md
Last active November 7, 2024 10:04
MySQL CLI Cheatsheet
@rxin
rxin / ByteBufferPerf.scala
Last active May 14, 2018 21:27
Comparison of performance over various approaches to read Java ByteBuffer. The best way is to use Unsafe, which also enables reading multiple primitive data types from the same buffer.
/**
* To compile:
* scalac -optimize ByteBufferPerf.scala
*
* JAVA_OPTS="-Xmx2g" scala IntArrayPerf 10
* 49 62 48 45 48 45 48 50 47 45
*
* JAVA_OPTS="-Xmx2g" scala ByteBufferPerf 10
* 479 491 484 480 484 481 477 477 472 473