The Eight Fallacies of Distributed Computing The network is reliable. Latency is zero. Bandwidth is ...

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The Eight Fallacies of Distributed Computing
The network is reliable.
Latency is zero.
Bandwidth is infinite.
The network is secure.
Topology doesn't change.
There is one administrator.
Transport cost is zero.
The network is homogeneous.
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7 Mistakes You’re Making In Your Programming Career 1. Not having a clear goal 2. Not investing in ...

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7 Mistakes You’re Making In Your Programming Career
1. Not having a clear goal

2. Not investing in non-technical or “soft skills”
people skills, mental stability, focus and self-motivation
how to prioritize and how to be as productive as possible
health and fitness, financial acumen

3. Not being part of the community
Being part of something larger than yourself, is a sure way to grow.

4. Not specializing
5. Not investing in your personal brand
6. Not working on a side-project

7. Not having a plan for self-education or continuous self-improvement.
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A blind Google engineer explains how he writes code http://ift.tt/1Ho9AiE...

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A blind Google engineer explains how he writes code
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Facebook Edgerank Algorithm (TBD) Affinity Score Edge Weight Time Decay Negative Feedback UeWeDe Edge...

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Facebook Edgerank Algorithm (TBD)
Affinity Score
Edge Weight
Time Decay

Negative Feedback
UeWeDe
Edge: action(One way), view posts, like a pgae, comment, tagged together
http://edgerank.net/
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How about Java8 on Android on Google/IO?

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How about Java8 on Android on Google/IO?


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CNET: LG Display shows off press-on 'wallpaper' TV under 1mm thick. http://ift.tt/1Saaec8...

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CNET: LG Display shows off press-on 'wallpaper' TV under 1mm thick. http://ift.tt/1Saaeca


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Hashmap change in Java 8: Using binary search tree when greater than TREEIFY_THRESHOLD The principal...

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Hashmap change in Java 8: Using binary search tree when greater than TREEIFY_THRESHOLD
The principal idea is that once the number of items in a hash bucket grows beyond a certain threshold(currently: TREEIFY_THRESHOLD = 8), that bucket will switch from using a linked list of entries to a balanced tree. In the case of high hash collisions, this will improve worst-case performance from O(n) to O(log n).
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If hashes are equal, HashMap hopes that the keys are Comparable, so that it can establish some order. 
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a shared underlying storage
Shared empty table in ArrayList and HashMap update
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static final Object[] EMPTY_ELEMENTDATA = {};


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XML External Entity Attack(XXE) http://ift.tt/Z2O0zd...

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XML External Entity Attack(XXE)
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Solutions:
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dbf.setFeature(XMLConstants.FEATURE_SECURE_PROCESSING, true);

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xif.setProperty(XMLInputFactory.IS_SUPPORTING_EXTERNAL_ENTITIES, false);
xif.setProperty(XMLInputFactory.SUPPORT_DTD, false);


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The Twelve-Factor App VI. Processes stateless and share-nothing Sticky sessions are a violation of twelve...

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The Twelve-Factor App
VI. Processes
stateless and share-nothing
Sticky sessions are a violation of twelve-factor and should never be used or relied upon. Session state data is a good candidate for a datastore that offers time-expiration, such as Memcached or Redis.

VII. Port binding
VIII. Concurrency

IX. Disposability
The twelve-factor app’s processes are disposable, meaning they can be started or stopped at a moment’s notice. 
all jobs are reentrant, which typically is achieved by wrapping the results in a transaction, or making the operation idempotent.

X. Dev/prod parity
XI. Logs: Logplex and Fluent, Splunk
XII. Admin processes
http://12factor.net/


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Slate: Gorgeous, Algorithmically Generated Time-Lapses of the World's Most Popular Landmarks. http:/...

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Slate: Gorgeous, Algorithmically Generated Time-Lapses of the World's Most Popular Landmarks. http://ift.tt/1JuOaoX


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19.05.2015 04:21

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Lucene/Solr Search Similarity tf(t in d) correlates to the term's frequency, defined as the number of...

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Lucene/Solr Search Similarity
tf(t in d) correlates to the term's frequency, defined as the number of times term t appears in the currently scored document d. Documents that have more occurrences of a given term receive a higher score. 
Math.sqrt(freq)

idf(t) stands for Inverse Document Frequency. This value correlates to the inverse of docFreq (the number of documents in which the term t appears). This means rarer terms give higher contribution to the total score
Math.log(numDocs/(double)(docFreq+1)) + 1.0

Query Coordination
coord(q,d) is a score factor based on how many of the query terms are found in the specified document. Typically, a document that contains more of the query's terms will receive a higher score than another document with fewer query terms. - computed at search time
overlap / (float)maxOverlap

The coordination factor (coord) is used to reward documents that contain a higher percentage of the query terms. The more query terms that appear in the document, the greater the chances that the document is a good match for the query.

queryNorm(q) is a normalizing factor used to make scores between queries comparable. This factor does not affect document ranking (since all ranked documents are multiplied by the same factor), but rather just attempts to make scores from different queries (or even different indexes) comparable.
1.0 / Math.sqrt(sumOfSquaredWeights)
The sumOfSquaredWeights is calculated by adding together the IDF of each term in the query, squared.

t.getBoost() is a search time boost of term t in the query q as specified in the query text

Index-Time Field-Level Boosting
We strongly recommend against using field-level index-time boosts

norm(t,d) encapsulates a few (indexing time) boost and length factors:
Field boost - set by calling field.setBoost() before adding the field to a document.
lengthNorm(Field-length norm)- computed when the document is added to the index in accordance with the number of tokens of this field in the document, so that shorter fields contribute more to the score. LengthNorm is computed by the Similarity class in effect at indexing.

DefaultSimilarity extends TFIDFSimilarity
Boolean Model
Vector Space Model
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Reshared post from Linux Life:

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17.05.2015 07:05

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