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.phony: run

run: thread.wasm
	wasmtime run --wasm-features threads --wasi-modules experimental-wasi-threads ./thread.wasm

thread.wasm: thread.wat
	wat2wasm --debug-names --enable-threads thread.wat

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public class HelloWorld {

    public static void main(String[] args) {
        System.out.println("Hello, World!");
    }
}

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Install service

Since this linux is an old version, it still use sysv scripts for service management. To run tailscaled as a daemon (service), follow the procedure below.

1. Copy the script to /etc/rc0.d/K20tailscaled. The script is mainly borrowed from this gist.
2. Adjust the script as appropriate.
3. Reboot the system via reboot.
4. Check the service is started.
   1. By listing all services with service --status-all.
   2. Or check the status of this specific service with service tailscaled status. If it's alright, you should get the following output.

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# builtin functions

# graph is a builtin module exposed by the host environment
# graph.nodes = {}
# graph.edges = []


def node(name, operation, conf={}, predicate=None):
    """
    :rtype: str the node name is returned

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package example

import com.google.common.collect.{ImmutableCollection, ImmutableList, ImmutableMap}
import net.starlark.java.annot.{Param, StarlarkBuiltin, StarlarkMethod}
import net.starlark.java.eval.{Dict, EvalException, Module, Mutability, Starlark, StarlarkFunction, StarlarkInt, StarlarkList, StarlarkSemantics, StarlarkThread, Structure, Tuple}
import net.starlark.java.syntax.{FileOptions, ParserInput}

import scala.collection.mutable.ListBuffer

object StarlarkDemo extends App {

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Playground

• Install wazero with the following commmand.

  go get github.com/tetratelabs/wazero@latest

• Download the wasm file of a Javascript interpreter. For simplicity, the following ways are listed.

  • If you have wapm installed, you could download one with

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Build a persistent, high availability and low latency key-value storage engine for derived data. One of such use cases is feature store. These use cases share some common characteristics, that we could utililze to build a better performing database.

1. The data is derived, so no need to handle replication or data recovery.
2. All the writes are through bulk loading, so no concurrency control needed.

In summary, it's like a scalable cache engine.

Features

• High throughput bulk load

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Prerequisites

1. Install graalvm.

sdk install java 22.3.r19-grl

2. Change current JVM to graalvm.

sdk use java 22.3.r19-grl

3. Install Graal js following the guide.

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It follows the interface (trait) oriented programming style.

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Fetch the following csv files and get top 10 rating movies.

https://gist.githubusercontent.com/CatTail/18695526bd1adcc21219335f23ea5bea/raw/54045ceeae6a508dec86330c072c43be559c233b/movies.csv