fnky

ANSI Escape Sequences

Standard escape codes are prefixed with Escape:

• Ctrl-Key: ^[
• Octal: \033
• Unicode: \u001b
• Hexadecimal: \x1B
• Decimal: 27

suxue

#include <boost/flyweight.hpp>
#include <boost/multi_index_container.hpp>
#include <boost/multi_index/member.hpp>
#include <string>
#include <cstdint>
#include <vector>
#include <iostream>
#include <tuple>

typedef std::tuple<short, std::uint8_t, std::uint8_t> Date;

robertdale

// This can be imported via ./bin/gremlin.sh -i describe.groovy
// A variable 'graph' must be defined with a JanusGraph graph
// Run it as a plugin command ':schema'
// :schema describe
// 

import org.janusgraph.graphdb.database.management.MgmtLogType
import org.codehaus.groovy.tools.shell.Groovysh
import org.codehaus.groovy.tools.shell.CommandSupport

yurishkuro

• What do Etcd, Consul, and Zookeeper do?
  • Service Registration:
    • Host, port number, and sometimes authentication credentials, protocols, versions numbers, and/or environment details.
  • Service Discovery:
    • Ability for client application to query the central registry to learn of service location.
  • Consistent and durable general-purpose K/V store across distributed system.
    • Some solutions support this better than others.
    • Based on Paxos or some derivative (i.e. Raft) algorithm to quickly converge to a consistent state.
• Centralized locking can be based on this K/V store.

dusenberrymw

Spark Tips & Tricks

Misc. Tips & Tricks

• If values are integers in [0, 255], Parquet will automatically compress to use 1 byte unsigned integers, thus decreasing the size of saved DataFrame by a factor of 8.
• Partition DataFrames to have evenly-distributed, ~128MB partition sizes (empirical finding). Always err on the higher side w.r.t. number of partitions.
• Pay particular attention to the number of partitions when using flatMap, especially if the following operation will result in high memory usage. The flatMap op usually results in a DataFrame with a [much] larger number of rows, yet the number of partitions will remain the same. Thus, if a subsequent op causes a large expansion of memory usage (i.e. converting a DataFrame of indices to a DataFrame of large Vectors), the memory usage per partition may become too high. In this case, it is beneficial to repartition the output of flatMap to a number of partitions that will safely allow for appropriate partition memory sizes, based upon the

nzw0301

*2vec papers

1. act2vec, trace2vec, log2vec, model2vec https://link.springer.com/chapter/10.1007/978-3-319-98648-7_18
2. apk2vec https://arxiv.org/abs/1809.05693
3. app2vec http://paul.rutgers.edu/~qma/research/ma_app2vec.pdf
4. ast2vec https://arxiv.org/abs/2103.11614
5. attribute2vec https://arxiv.org/abs/2004.01375
6. author2vec http://dl.acm.org/citation.cfm?id=2889382
7. baller2vec https://arxiv.org/abs/2102.03291
8. bb2vec https://arxiv.org/abs/1809.09621

EthanRosenthal

from numpy.linalg import solve

class ExplicitMF():
    def __init__(self, 
                 ratings, 
                 n_factors=40, 
                 item_reg=0.0, 
                 user_reg=0.0,
                 verbose=False):
        """

joar

# Add field
echo '{"hello": "world"}' | jq --arg foo bar '. + {foo: $foo}'
# {
#   "hello": "world",
#   "foo": "bar"
# }

# Override field value
echo '{"hello": "world"}' | jq --arg foo bar '. + {hello: $foo}'
{

hyper0x

package main

import (
	"bufio"
	"bytes"
	"fmt"
	"io"
	"log"
	"net"
	"os"

freemo

import com.thinkaurelius.titan.core.TitanFactory;
import com.thinkaurelius.titan.core.TitanGraph;
import com.thinkaurelius.titan.core.TitanKey;
import com.thinkaurelius.titan.core.attribute.Geoshape;
import com.thinkaurelius.titan.graphdb.configuration.GraphDatabaseConfiguration;
import com.tinkerpop.blueprints.Edge;
import com.tinkerpop.blueprints.Vertex;
import com.tinkerpop.blueprints.util.ElementHelper;
import org.apache.commons.configuration.BaseConfiguration;
import org.apache.commons.configuration.Configuration;