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ARG FUNCTION_RUNTIME

FROM mikesir87/aws-cli as code

ARG FUNCTION_NAME
ARG AWS_DEFAULT_REGION
ARG AWS_ACCESS_KEY_ID
ARG AWS_SECRET_ACCESS_KEY

RUN wget -O function.zip `aws lambda get-function --function-name $FUNCTION_NAME --query 'Code.Location' --output text`

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import pickle
import numpy as np
import multiprocessing as mp

a = np.array([1,2,3], dtype=np.uint32)
b = np.array([1,2,3], dtype=np.uint32)
c = np.array([1,2,3], dtype=np.uint32)
d = np.array([1,2,3], dtype=np.uint32)

q = mp.Queue()

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Next Steps

• Measure time spend on index, flush, refresh, merge, query, etc. (TD - done)
• Take hot threads snapshots under read+write, read-only, write-only (TD - done)
• Adjust refresh time to 10s (from 1s) and see how load changes (TD)
• Measure time of a rolling restart doing disable_flush and disable_recovery (TD)
• Specify routing on query -- make it choose same node for each shard each time (MD)
• GC new generation size (TD)
• Warmers

• measure before/after of client query time with and without warmers (MD)

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/**
 * Based off of the Lucene prolog parser in the wordnet contrib package within the
 * main Lucene project. It has been modified to remove the Lucene bits and generate
 * a synonyms.txt file suitable for consumption by Solr. The idea was mentioned in
 * a sidebar of the book Solr 1.4 Enterprise Search Server by Eric Pugh.
 * 
 * @see <a href="http://lucene.apache.org/java/2_3_2/lucene-sandbox/index.html#WordNet/Synonyms">Lucene Sandbox WordNet page</a>
 * @see <a href="http://svn.apache.org/repos/asf/lucene/dev/trunk/lucene/contrib/wordnet/">SVN Repository of the WordNet contrib</a>
 * @see <a href="https://www.packtpub.com/solr-1-4-enterprise-search-server/book">Solr 1.4 Enterprise Search Server Book</a>
 */

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#!/bin/sh
BUCKETNAME=mybucketname; REGION=us-east-1; for prefix in $(aws s3api list-objects --bucket $BUCKETNAME --delimiter '/' --output text --region $REGION |grep COMMONPREFIX |tail -n+2| awk '{print $2}'); do echo "Totals for $prefix"; aws s3 ls --summarize --human-readable --recursive s3://$BUCKETNAME/$prefix --region $REGION ; done |grep Total

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def load_bin_vec(fname, vocab):
    """
    Loads 300x1 word vecs from Google (Mikolov) word2vec
    """
    word_vecs = {}
    with open(fname, "rb") as f:
        header = f.readline()
        vocab_size, layer1_size = map(int, header.split())
        binary_len = np.dtype('float32').itemsize * layer1_size
        for line in xrange(vocab_size):

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import numpy as np
import theano
import theano.tensor as T
from theano import ifelse
from .. import init
from .. import nonlinearities

from .base import Layer

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sudo apt-get install libc6:i386 libstdc++6:i386 zlib1g:i386 libx11-6:i386 libxext6:i386 libxrender1:i386

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from functools import partial
from theano.ifelse import ifelse
import numpy as np
import theano
import theano.tensor as T

def maxx(e):
    return ifelse(T.gt(e, 0.0), e, 0.0)

def s(x, y, U):