schmohlio

  import com.google.gson.Gson
  import java.util.{Map => JMap, LinkedHashMap}

  type GenericDecoder = String => JMap[String, Object]

  val decoder: GenericDecoder = {
    // Gson instances are apparently thread-safe, so curry...
    val gson: Gson = new Gson()
    // LinkedHashMap preserves ordering. use HashMap if not required.
    x => gson.fromJson(x, (new LinkedHashMap[String, Object]()).getClass)

schmohlio

open Newtonsoft.Json
    let rec private _flattenJson (delim:string) (pkey:string) (json:JsonValue): (string * JsonValue) seq =
        json.Properties
        |> Seq.collect (fun (k, v) ->
            match v with
            | JsonValue.Record r -> _flattenJson delim k (JsonValue.Record r)
            | _ -> [(pkey + delim + k, v)] |> Seq.ofList
        )

    /// flatten a Json nested children and stop at primitive or Array. specify delimiter for nested key names.

schmohlio

#!/bin/bash -e
""" USAGE: ./remove_empty_part_files.sh <qualified hdfs dir path> """
HDFS=$1

echo "checking for empty files in $HDFS..."
IFS=$'\n'
for i in `hadoop fs -ls $HDFS/* | grep -e "$HDFS/.*" | awk '{print $0}'` ; do
  file=$(echo $i | awk '{print $8}')
  size=$(echo $i | awk '{print $5}')
  if [ $size -eq 0 ]; then

schmohlio

XBuild Engine Version 12.0
Mono, Version 4.2.0.0
Copyright (C) 2005-2013 Various Mono authors
Loading default tasks for ToolsVersion: 4.0 from /usr/local/Cellar/mono/4.2.0.179/lib/mono/4.5/Microsoft.Common.tasks

Build started 1/27/2016 9:48:30 AM.
__________________________________________________
Extension path '/Library/Frameworks/Mono.framework/External/xbuild' not found, ignoring.
Extension path '/Library/Frameworks/Mono.framework/External/xbuild' not found, ignoring.
Project "MYPROJECT.fsproj" (default target(s)):

schmohlio

A state machine is defined as follows:

• Input - a set of inputs
• Output - a set of outputs
• State - a set of states
• S0 ∈ S - an initial state
• T : Input * State -> Output * State - a transition function

If you model your services (aggregates, projections, process managers, sagas, whatever) as state machines, one issue to address is management of State. There must be a mechanism to provide State to the state machine, and to persist resulting State for subsequent retrieval. One way to address this is by storing State is a key-value store. Another way is to use a SQL database. Yet another way is event sourcing. The benefit of even sourcing is that you never need to store State itself. Instead, you rely on the Output of a service to reconstitute state. In order to do that, the state machine transition function needs to be factored into two functions as follows:

schmohlio

#!/usr/bin/env python

'''
    DataSync

    Makes instructions to copy datasets to servers missing backups
    based on input data.

    - Ensure that each data center has a copy of every data set.
    - Every dataset is included in at least 1 data center.

schmohlio

#!/usr/bin/env python

'''
    JumbleSorter.py

    sorts a list of strings and integers, but keeps types at nth element
    in list constant in result.

    only implement for stdin for now, i.e.,

schmohlio

meetings_sample = [(0, 30), (60, 90), (20, 65)]
[(0,True),(30,False),(60,True),(90,False),(20,True),(65,False)]

def count_rooms(meeting_events):
    meeting_events.sort(lambda x,y: x[0]<y[0]) # O(nlogn), need to add sorting here so that False is first
    # not sure if that sort is left associative or right 
    # associative
    ongoing_meetings = [] # pretend stack
    max_num_meetings = 0 # initialize
    stack_size = 0

schmohlio

val sample = List(1,2,3,3,5,4,6,7,4)
 
// a good default if sample is always positive integers.
val START = (-1, -1) 

// this is what I meant by default foldLeft (or scanLeft) value
val two_largest = test.foldLeft(START) { (acc: (Int, Int), n: Int) =>
  val (smaller, larger) = acc
  if (n > larger) 
    (larger, n)

schmohlio

/** 
* @keys     n-length list of "labels", where the @key[i] is the category label of the ith level of @dat
* @dat      a nested associative array, tree-like, with n+1 levels, where 1..n levels of the tree represent categories
*           and the n+1 level is the actual request data. 
* returns:  list of associative arrays, each representing rows to be inserted into database.
*
*   flattens nested array into a list of "rows", where the |rows| == |leaves in tree|.
*   each "row" contains the data within the leaves, plus n additional key-value pairs represented by
*   label => category (i.e. [...country => 'US', type => 'tablet'] when @keys = ['country', 'type'], and @dat has n+1==3 levels.)
**/