Hi There,
I'm Saurav Mukherjee
i am into
About MeSecond-year CSE Undergraduate Student at Asansol Engineering College. Founder and Event Organizer at (CodeIN) Community of Coding Enthusiasts. Along with a wonderful team, I lead the center for entrepreneurial leadership at my college. Skills: Data Science, Front-end development, Machine learning, Microsoft Azure, Deep learning, jQuery and Google cloud. Known Languages: Python,Java, C++, C, Java, HTML, CSS,JavaScript. I run two Youtube channels called 'Me Sourav Official' and 'Saurav Mukherjee' which have garnered over 20,000 views.
age: 20
college : Asansol Engineering College
email<EMAIL_ADDRESS>place : Asansol, India-713305
Education is not the learning of facts, but the training of the mind to think.
Feb 2021 - March 2021
Worked on Supervised Machine learning In this regression task, we have predicted the percentage of marks that a student is expected to score based upon the number of hours they studied.
April 2021 - June 2021
Mentored 10 mentees under the Skills Spring Mentorship Program in Machine learning Domain held by Skills Springs, an initiative of Skills Nights, Indian Institute Of Information Technology Nagpur (IIITN).
Aug 2021 - Present
ConnectBud Tutor | Live 1:1 Online Coding Classes for Kids.
July 2021 - Present
Created Basic Banking System Website for The Sparks Foundation this is a simple credit management system given in sparks foundation internship program..
May 2021 - June 2021
During the program, I have completed 120+ google Qwiklabs to complete the Milestone and received swags from Google.


#include <db.h>int db_appinit(char *db_home, char *db_config, DB_ENV *dbenv, u_int32_t flags);
The db_appinit function provides a simple way to initialize and configure the Berkeley DB environment. It is not necessary that it be called, but it provides a structure for creating a consistent environment for processes using one or more of the features of Berkeley DB.
The db_home and db_config arguments to db_appinit are described in Berkeley DB File Naming.
The flags argument specifies the subsystems that are initialized and how the environment affects Berkeley DB file naming, among other things. The flags value is specified by logically OR'ing together one or more of the following values:
The db_appinit function returns successfully if DB_RECOVER is
specified and no log files exist, so it is necessary to ensure all
necessary log files are present before running recovery.
For further information, consult db_archive and db_recover.
The db_appinit function returns successfully if DB_RECOVER_FATAL
is specified and no log files exist, so it is necessary to ensure all
necessary log files are present before running recovery. For further
information, consult db_archive and db_recover.
The Berkeley DB environment is configured based on the dbenv argument to db_appinit which is a pointer to a structure of type DB_ENV. Applications normally use the same DB_ENV structure (initialized by db_appinit) as an argument to all of the subsystems in the Berkeley DB package.
References to the DB_ENV structure are maintained by Berkeley DB, so it may not be discarded until the last close function, corresponding to an open function for which it was an argument, has returned. To ensure compatibility with future releases of Berkeley DB, all fields of the DB_ENV structure that are not explicitly set should be initialized to 0 before the first time the structure is used. Do this by declaring the structure external or static, or by calling one of the C library routines bzero(3) or memset(3).
The fields of the DB_ENV structure used by db_appinit are described below. The dbenv argument may not be NULL. If any of the fields of the dbenv structure are set to 0, defaults appropriate for the system are used where possible.
The following fields in the DB_ENV structure may be initialized before calling db_appinit:
If db_paniccall is non-NULL and such an error occurs, it will
called. The dbenv argument is a reference to the current
environment, and the errval argument is the system errno value
that was returned when the error occurred.
If db_errcall is non-NULL, it may be called with additional error
information. The db_errpfx argument is the current environment's
db_errpfx field. The buffer argument contains a
nul-terminated string with the additional information.
This error logging facility does not slow performance or significantly
increase application size, and may be run during normal operation as
well as during debugging.
except that the error message is written to the OutputStream
represented by error_stream.
allowing errors to be
redirected to a C++ error stream. It is unwise to use both error_stream
with nonzero values of either errcall or errfile.
Each of the open functions that db_appinit may call (lock_open, log_open, memp_open and txn_open), is called as follows, where the DB_CREATE flag is optional:
XXX_open(NULL, DB_CREATE, S_IRUSR | S_IWUSR | S_IRGRP | S_IWGRP, dbenv);
This call will cause each subsystem to construct pathnames as described in Berkeley DB File Naming. The subsystem has permission to read and write underlying files as necessary, and optionally to create files. (All created files will be created readable and writeable by the owner and the group. The group ownership of created files is based on the system and directory defaults, and is not further specified by Berkeley DB.)
In addition, the dbenv argument is passed to the open functions of any subsystems initialized by db_appinit. For this reason the fields of the DB_ENV structure relevant to the subsystems being initialized must themselves be initialized before db_appinit is called. See the appropriate subsystem documentation for a list of these fields and their uses.
The return value from each of these calls is placed in the appropriate field of the DB_ENV structure:
In general, these fields are not directly used by applications; subsystems of Berkeley DB that use these fields simply reference them using the DB_ENV structure passed to the subsystem.
For example, an application using the Berkeley DB hash access method functions to access a database will first call db_open passing it the DB_ENV argument initialized by a call to db_appinit. Then, all future calls to the hash access method functions for that database will automatically use the underlying shared memory buffer pool that was specified by the mp_info field of that DB_ENV structure.
The single exception to this rule is the tx_info field, which applications must explicitly specify to the txn_begin, txn_checkpoint and txn_close functions.
The db_prefix field of DB_ENV allows the user to configure the error message prefix, and may be changed at any time, including after the call to db_appinit.
Otherwise, once the Berkeley DB environment has been initialized by a call to db_appinit, no fields should be modified.
On Windows/95, files that are opened by multiple processes do not share data correctly. To cause Berkeley DB to use the paging file to share memory among processes, use the DB_REGION_NAME flag of the db_value_set function. Obviously, you do not need to do this if only a single process will be accessing database files.
The db_appinit function returns the value of errno on failure, and 0 on success.
The db_appinit function may fail and return errno for any of the errors specified for the following Berkeley DB and C library functions: DB->close, abort(3), ctime(3), db_appexit, dbenv->tx_recover(3), fclose(3), fcntl(3), fflush(3), fgets(3), fopen(3), fprintf(3), free(3), getenv(3), getpid(3), getuid(3), isspace(3), lock_open, lock_unlink, log_compare, log_get, log_open, log_unlink, malloc(3), memcpy(3), memp_open, memp_unlink, memset(3), realloc(3), stat(3), strcat(3), strchr(3), strcmp(3), strcpy(3), strlen(3), time(3), txn_checkpoint, txn_open, txn_unlink, vfprintf(3), and vsnprintf(3).
In addition, the db_appinit function may fail and return errno for the following conditions:
The DB_THREAD flag was specified and spinlocks are not implemented for this architecture.
The DB_HOME or TMPDIR environment variables were set but empty.
An incorrectly formatted NAME VALUE entry or line was found.


Select a file to use as source for loading data. At the moment, CSV is the only supported file-format. The file should contain a header-row to be able to map the fields to node-fields
Select which fields that should be included, and also the data-types If selecting a latitude or longitude value-type, you must specify the matching latitude/longitude to create a geo-point
Load a source
Depending on your mapping-settings, other settings are set here:
Select the repository you are going to load data into
Create a repository with default settings
Running and newly finished jobs:
No jobs


These are primarily the CS based projects completed taking the Berkeley CS 61A-C series.
CS 61A: (Python) Structure and Interpretation of Computer Programs [Introduction]
CS 61B: (Java) Data Structures
CS 61C: (C) Machine Structures
VSee is a search engine designed to help startups more easily find Venture Capital (VC) Firms. VSee's information was scraped from Venture Capital sights, such as cbinsights.com. This information was then stored into an Elasticsearch Django stack run on an Amazon EC2 server. With this we developed an algorithm based on the location, funding round, and market of a startup to match them with VC's. The goal was to make it easier for startups to find potential funding.
Hog is a dice game played between two players in which the players choose how many dice to roll baed on optimal strategy. The goal for this project was to write a program which won more than 60% of the time against a random computer based on proper selection of dice to roll.
Trends was a project based on Twitter Tweets around the US. We parsed through Tweets to find trends in the data. We primarily compared geographic location data to sentiment data from tweets to determine states with different overall positive and negative sentiments.
Ants is a tower defense game, wherein ants protect a tower against bees. We designed varying algorithms to enable different abilties for each of the characters in the game. The project tied in several object-orientated programming paradigms, and involved understanding testing a large program with many related parts.
In this project we created a Scheme interpreter for a subset of the Scheme language using Python. We also implemented some small Scheme programs to run with this interpreter.
Ocean was a simulation of an ocean containing fish and sharks. Both fish and shark had several properties based on their surrondings and species of whether they would survive or not. We also wrote code to convert the entire ocean into a run-length encoding.
In this we implemented a program which plays the game Network against a human or other computer program. Network is an 8x8 board game played to create a "Network" across the board. This project was heavily based around game theory, breadth, and depth first search algorithms.
The purpose of this project was to become comfortable with applications that combine a variety of data structures and algorithms in a big ol' mess of references pointing just every which way. Using past data structures (Disjoint Sets and Linked Lists), we created a graph and tree data structure with functions for usability such as a neighbor() function.
We used a MapReduce Strategy to answer a big data problem. We calculcated co-occurences amoung words in documents. The end result of this project was run on Amazon EC2 servers using Hadoop.
We created an instruction interpreter for a subset of MIPS code. This project allowed us to become more familiar with MIPS and C programming.
The goal was to optimize a formula for a 2D convultion on images. The tricks we used for the optimization included Register Blocking, Loop Ordering, SSE Intructions, Loop Unrolling, OpenMP, and Compiler Tricks.
Using Logism, we created a 16-bit two-cycle processor similar to MIPS. We designed an Arithmetic Logic Unit, a Register, and the CPU for this project.


|
My Project
|
A breakpoint object. More...
#include <emulate.hh>
Public Member Functions | |
| BreakCallBack (void) | |
| Generic breakpoint constructor. More... | |
| virtual bool | pcodeCallback (PcodeOpRaw *op) |
| Call back method for pcode based breakpoints. More... | |
| virtual bool | addressCallback (const Address &addr) |
| Call back method for address based breakpoints. More... | |
| void | setEmulate (Emulate *emu) |
| Associate a particular emulator with this breakpoint. More... | |
Protected Attributes | |
| Emulate * | emulate |
| The emulator currently associated with this breakpoint. | |
A breakpoint object.
This is a base class for breakpoint objects in an emulator. The breakpoints are implemented as callback method, which is overridden for the particular behavior needed by the emulator. Each derived class must override either
depending on whether the breakpoint is tailored for a particular pcode op or for a machine address.
|
inline |
Generic breakpoint constructor.
The base breakpoint needs no initialization parameters, the setEmulate() method must be called before the breakpoint can be invoked
|
inlinevirtual |
Call back method for address based breakpoints.
This routine is invoked during emulation, if this breakpoint has somehow been associated with this address. The callback can perform any operation on the emulator context it wants. It then returns true if these actions are intended to replace the action of the entire machine instruction at this address. Or it returns false if the machine instruction should still be executed normally.
| addr | is the address where the break has occurred |
Reimplemented in TerminateCallBack, PrintfCallBack, and PutsCallBack.
|
inlinevirtual |
Call back method for pcode based breakpoints.
This routine is invoked during emulation, if this breakpoint has somehow been associated with this kind of pcode op. The callback can perform any operation on the emulator context it wants. It then returns true if these actions are intended to replace the action of the pcode op itself. Or it returns false if the pcode op should still have its normal effect on the emulator context.
| op | is the particular pcode operation where the break occurs. |
|
inline |
Associate a particular emulator with this breakpoint.
Breakpoints can be associated with one emulator at a time.
| emu | is the emulator to associate this breakpoint with |


New blog
Hey All,
So I finally got around to making a new blog, as blogger was getting too hard to write anything lengthy that included code snippets
I found Jekyll, which is super simple to use, supports markdown (I’m a big fan of md) and supports code/syntax highlighting and formatting out of the box. You can also host at github for free! (thanks Github)
Checkout markdown cheat sheet and github pages to get started.
Also, my blog previously was mainly about things related to my raspberry pi and doing cool things with it, while this will still be the main theme, I will also be posting about random stuff I find too. Have a lot of cool things to share, so hopefully will have plenty of content coming soon!


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IMDB Rating {{movie.imdbRating}} ({{movie.imdbVotes}} votes)
Year: {{movie.Year}}
Rated: {{movie.Rated}}
Released: {{movie.Year}}
Runtime: {{movie.Runtime}}
Genre(s): {{movie.Genre}}
Country: {{movie.Country}}
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mdl = __import__("dynamic_plugin")
sys.exit(0)
except Exception as e:
print("Failed to import the dynamic plugin.")
sys.exit(1)
finally:
//
// clean up.
print("Attempting to import dynamic_plugin...")
mdl = __import__("dynamic_plugin")
except ImportError:
raise SystemExit("Failed to import the dynamic plugin.")
finally:
// Clean up. Remove files dynamic_plugin.py[c]
try:
os.remove(plugin_filename)


Tue Dec 24, 2019
It’s already time for a year-end wrap up.  But I intend to remedy this oversight; it’s clichéd, easy, and fun - so why the hell not?
There are plenty of important, serious topics that dominated the conversation in 2019. But I’m not going to talk about any of them.
Instead, I’m going to talk about foldable phones, fake airpods, and cybertrucks - three uniquely 2019 ways for the important man to cultivate an air of swaggering braggadocio. Ladies and gentleman, this is how you flex in 2019.
And then I’ll wrap up by discussing the best game, book, and movie I played, read, and watched this year. To be clear, my faves may not have hit the shelves in 2019, but they’re new for me - and these top picks get my thumbs up for a high enjoyment factor at any time.
Sound good? Let’s get started.
Before 2019, folding phones were the stuff of science fiction. The most realistic of these fantasy foldables has to be the tri-fold device from Westworld. When these puppies pop up in this excellent show, you can really see the appeal of a smartphone-tablet hybrid that you can fold up and put in your pocket.
Now these things are for real - and that fact alone tastes like awesome sauce. The flavour of awesome sauce reminiscent of the first iPad release when another Star Trek gadget came to life.
The first mainstream foldable on the market is the Samsung Galaxy Fold. What isn’t so delicious is the price - a buzz-killing $2,599 in Canada. Not only is that price prohibitive, but the Galaxy Fold isn’t exactly robust.  Let’s just say you should never under any circumstances take this thing to the beach.
But go ahead and buy the Fold if you smile smugly at jealous eyes, if you’re keen to preen, if you want the world to see you flush almost three grand away without even looking into your diamond-encrusted toilet bowl. For everybody else - relax - it’s early days in a nascent product category.
For me, the recently-announced Motorola Razr reboot really hits that foldable sweet spot. These guys worked for four flipping years (sorry) on their hinge design. But flipping the Razr open or closed seems just as satisfying as it was in 2004. A device that folds up into such a pocketable form factor is a definite throwback to the good old days but with the futuristic boon of all that extra screen real estate. And there doesn’t even seem to be much of a crease at the fold.
The new Razr will only be available in 2020 but once again the price is up there - around $2000 Canadian - making this one of the most expensive phones you can buy. I’d say the prestige of owning one of these definitely puts it firmly in flex territory.
However, if you’re desperate to flex but have no cash, enter into the wonderfully seedy world of Chinese knockoffs. I’ve recently gotten more into the overwhelming mess of a marketplace that is Aliexpress. It’s amazing.
You could pick up an iPhone 11 Pro replica for $160, but really, why would you? It may look just like an iPhone, but it most definitely doesn’t perform like an iPhone. That is the very definition of needless suffering just so you can impress precisely no one. And for that kind of money, you’d have to be really invested in the farce.
Airpod replicas, however, are surprisingly good. Not only do they cost next to nothing and are indistinguishable in appearance, but their performance is disgustingly close to the real thing (the disgust will come when you think about Apple’s profit markup).
Let’s be honest here - the Airpods have never sounded that good, so the performance bar wasn’t that hard to clear.
These unscrupulous yet clever clones even have a reverse-engineered H1 chip so that Apple’s slick pairing process is triggered in the iPhone software. And useful features like turning off the music when pulling an Airpod out of your ear are there.
This year, Airpods are right up there on the Christmas wish list for teenagers. They’ve become a status symbol in high schools and on University campuses across North America. Apple have doubled their production just to keep up with demand.
So, if you have teenagers who are bullied mercilessly for wearing wired earphones, there’s no reason to dip into their college fund to ensure they fit in amongst their peers. Get them a couple of Airpod clones from Aliexpress - everybody will be happy (even though you may be paving over bigger problems in your troubled family’s life).
However, if you’re like me and don’t care for the Airpods design, there are some really impressive True Wireless Stereo (TWS) earbuds on Aliexpress for around $20. I recently picked up a pair of the well-regarded Haylou GT1 Pros and really dig how light, unobtrusive, and portable they are. The sound quality is decent - better than similarly-priced TWS buds (but obviously not as good as an expensive pair of over-the-ear headphones). And they sound better than Airpods.
Of course, Apple has recently upped their wireless-earbud game with the Airpods Pro which rights the Airpod wrongs and are much more advanced. If you’re looking for great Airpod Pro clones, you’re out of luck - these will be hard to beat. If you’re trying to look cool, you’d better hope the prestige doesn’t shift to the Pros; soon Airpod wearers could look like paupers.
Now, if you actually are extremely well-off, don’t necessarily care about image, but love avant-garde tech, you’ll probably be getting the Tesla Cybertruck. In which case, you’ll be flexing hard whether you want to or not.
Do you really need a brutalist, bulletproof mutant delorean crafted from the same stainless-steel alloy used on SpaceX rocket ships? Perhaps not, but you will be dystopian-future proof.
There may be a Ford F150 parked in every driveway in middle America right now, but Elon envisions a fleet of techno-demon nightmares pouring out of yuppie enclaves on the East and West coasts and invading America’s heartland. Or perhaps he is preparing ground transport for his Mars colony. Whatever he is thinking, he is definitely thinking out of the box.
Count me into the “love it” camp of the Cybertruck’s polarizing design. Although I’ll never be able to afford it, or have the space for it (this beast is beefier than a Hummer), I’m into it. If only to imagine what a cool Dad I’d be dropping the kids off at school in what is effectively a kid’s drawing of a robot car come to life.
The Cybertruck feels more like a harbinger of the next decade than a product born in 2019. It won’t, after all, come out until we’re well into the 2020s. And given Musk’s track record, even that seems optimistic. But, on the day I see Elon’s toy tank bruising the asphalt on our neighbourhood street, I’ll know the future has truly arrived.
Best of 2019
As promised, here are my personal top picks for media I consumed this year. And because it isn’t easy to pick just one, I’ll also throw in a runner-up honourable mention.
Best game: God of War
There is one one word that describes why this game is so good: polish. A fastidious amount of polish in the pacing, environment, combat and puzzles that is quite frankly missing in those bigger open-world games. The story is also very-well written and rich with Norse mythology.
There is simply no waste or fluff in God of War. The developers have even opted to preserve the perfection of their creation by not adding any DLC. This is a decision I fully support - most DLC is a cash grab.
Honourable mention: Spider-Man. Spider-Man is my childhood favourite, so how could I not enjoy web-swinging through New York.
Best book: Golden Son
The second book in the Red Rising trilogy, Golden Son is just too much fun. Pierce Brown is really good at flipping the script and subverting expectations. And with one of his influences being The Count of Monte Cristo (one of my favourite books of all time), how could I not enjoy the elaborate long game of infiltrating a society you’re going to overturn.
The first book in the trilogy was great, and not only is this sequel a refreshingly different story, but Brown has soundly beaten the sophomore curse and taken the series to the next level. I’m looking forward to reading the rest.
Honourable mention: Oathbringer. Brandon Sanderson’s most epic series to date is mind boggling in scope and execution.
Best movie: John Wick Chapter 3 - Parabellum
I had a blast watching the third John Wick. This movie is devoid of weighty expectations, fan-serving Easter Eggs, or Oscar-baiting monologues. There is something clean, simple, and deeply satisfying in just sitting back and enjoying the excellent choreography.
The John Wick movies have never taken themselves too seriously - after all the original catalyst for the spiralling bloodbath was the murder of John Wick’s dog.  And Keanu Reeves is just so likable and down-to-earth, it’s almost mandatory to support his resurgent career.
In 2021, both Matrix 4 and John Wick 4 are being released on the same day - they’re calling it Keanu Day. And I couldn’t be happier.
Honourable mention: Avengers: Endgame. If you watched all 23 interconnected Marvel movies to get to this point, how could you not watch this?
So, that’s it folks. Have a wonderful Christmas and a Happy New year! See you in 2020.


Class: Aws::Transfer::Types::As2ConnectorConfig
| Relationships & Source Files | |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Class Chain:
self,
Struct
|
|
|
Instance Chain:
self,
::Aws::Structure ,
Struct
|
|
| Inherits: |
Struct
|
| Defined in: | gems/aws-sdk-transfer/lib/aws-sdk-transfer/types.rb |
Overview
Contains the details for an AS2 connector object. The connector object
is used for AS2 outbound processes, to connect the ::Aws::Transfer
Family
customer with the trading partner.
Constant Summary
Instance Attribute Summary
-
#basic_auth_secret_id ⇒ String
rw
Provides Basic authentication support to the AS2 Connectors API.
-
#compression ⇒ String
rw
Specifies whether the AS2 file is compressed.
-
#encryption_algorithm ⇒ String
rw
The algorithm that is used to encrypt the file.
-
#local_profile_id ⇒ String
rw
A unique identifier for the AS2 local profile.
-
#mdn_response ⇒ String
rw
Used for outbound requests (from an
::Aws::Transfer
Family server to a partner AS2 server) to determine whether the partner response for transfers is synchronous or asynchronous. -
#mdn_signing_algorithm ⇒ String
rw
The signing algorithm for the MDN response.
-
#message_subject ⇒ String
rw
Used as the
Subject
HTTP header attribute in AS2 messages that are being sent with the connector. -
#partner_profile_id ⇒ String
rw
A unique identifier for the partner profile for the connector.
-
#signing_algorithm ⇒ String
rw
The algorithm that is used to sign the AS2 messages sent with the connector.
Instance Method Summary
::Aws::Structure
- Included
| #to_hash | Alias for Structure#to_h. |
Instance Attribute Details
#basic_auth_secret_id ⇒ String
(rw)
Provides Basic authentication support to the AS2 Connectors API. To
use Basic authentication, you must provide the name or Amazon
::Aws::Transfer::Resource
Name (ARN) of a secret in Secrets Manager.
The default value for this parameter is null
, which indicates that
Basic authentication is not enabled for the connector.
If the connector should use Basic authentication, the secret needs to be in the following format:
\{ "Username": "user-name", "Password": "user-password" \}
Replace user-name
and user-password
with the credentials for the
actual user that is being authenticated.
Note the following:
You are storing these credentials in Secrets Manager, not passing them directly into this API.
If you are using the API, SDKs, or
::Aws::CloudFormation
to configure your connector, then you must create the secret before you can enable Basic authentication. However, if you are using the Amazon Web Services management console, you can have the system create the secret for you.
If you have previously enabled Basic authentication for a connector,
you can disable it by using the UpdateConnector
API call. For
example, if you are using the CLI, you can run the following command
to remove Basic authentication:
update-connector --connector-id my-connector-id --as2-config
'BasicAuthSecretId=""'
# File 'gems/aws-sdk-transfer/lib/aws-sdk-transfer/types.rb', line 120
class As2ConnectorConfig < Struct.new( :local_profile_id, :partner_profile_id, :, :compression, :encryption_algorithm, :signing_algorithm, :mdn_signing_algorithm, :mdn_response, :basic_auth_secret_id) SENSITIVE = [] include Aws::Structure end
#compression ⇒ String
(rw)
Specifies whether the AS2 file is compressed.
# File 'gems/aws-sdk-transfer/lib/aws-sdk-transfer/types.rb', line 120
class As2ConnectorConfig < Struct.new( :local_profile_id, :partner_profile_id, :, :compression, :encryption_algorithm, :signing_algorithm, :mdn_signing_algorithm, :mdn_response, :basic_auth_secret_id) SENSITIVE = [] include Aws::Structure end
#encryption_algorithm ⇒ String
(rw)
The algorithm that is used to encrypt the file.
NONE
if the URL for your connector uses
HTTPS. This ensures that no traffic is sent in clear text.
# File 'gems/aws-sdk-transfer/lib/aws-sdk-transfer/types.rb', line 120
class As2ConnectorConfig < Struct.new( :local_profile_id, :partner_profile_id, :, :compression, :encryption_algorithm, :signing_algorithm, :mdn_signing_algorithm, :mdn_response, :basic_auth_secret_id) SENSITIVE = [] include Aws::Structure end
#local_profile_id ⇒ String
(rw)
A unique identifier for the AS2 local profile.
# File 'gems/aws-sdk-transfer/lib/aws-sdk-transfer/types.rb', line 120
class As2ConnectorConfig < Struct.new( :local_profile_id, :partner_profile_id, :, :compression, :encryption_algorithm, :signing_algorithm, :mdn_signing_algorithm, :mdn_response, :basic_auth_secret_id) SENSITIVE = [] include Aws::Structure end
#mdn_response ⇒ String
(rw)
Used for outbound requests (from an ::Aws::Transfer
Family server to a
partner AS2 server) to determine whether the partner response for
transfers is synchronous or asynchronous. Specify either of the
following values:
SYNC
: The system expects a synchronous MDN response, confirming that the file was transferred successfully (or not).NONE
: Specifies that no MDN response is required.
# File 'gems/aws-sdk-transfer/lib/aws-sdk-transfer/types.rb', line 120
class As2ConnectorConfig < Struct.new( :local_profile_id, :partner_profile_id, :, :compression, :encryption_algorithm, :signing_algorithm, :mdn_signing_algorithm, :mdn_response, :basic_auth_secret_id) SENSITIVE = [] include Aws::Structure end
#mdn_signing_algorithm ⇒ String
(rw)
The signing algorithm for the MDN response.
SigningAlgorithm
is used.
# File 'gems/aws-sdk-transfer/lib/aws-sdk-transfer/types.rb', line 120
class As2ConnectorConfig < Struct.new( :local_profile_id, :partner_profile_id, :, :compression, :encryption_algorithm, :signing_algorithm, :mdn_signing_algorithm, :mdn_response, :basic_auth_secret_id) SENSITIVE = [] include Aws::Structure end
#message_subject ⇒ String
(rw)
Used as the Subject
HTTP header attribute in AS2 messages that are
being sent with the connector.
# File 'gems/aws-sdk-transfer/lib/aws-sdk-transfer/types.rb', line 120
class As2ConnectorConfig < Struct.new( :local_profile_id, :partner_profile_id, :, :compression, :encryption_algorithm, :signing_algorithm, :mdn_signing_algorithm, :mdn_response, :basic_auth_secret_id) SENSITIVE = [] include Aws::Structure end
#partner_profile_id ⇒ String
(rw)
A unique identifier for the partner profile for the connector.
# File 'gems/aws-sdk-transfer/lib/aws-sdk-transfer/types.rb', line 120
class As2ConnectorConfig < Struct.new( :local_profile_id, :partner_profile_id, :, :compression, :encryption_algorithm, :signing_algorithm, :mdn_signing_algorithm, :mdn_response, :basic_auth_secret_id) SENSITIVE = [] include Aws::Structure end
#signing_algorithm ⇒ String
(rw)
The algorithm that is used to sign the AS2 messages sent with the connector.
# File 'gems/aws-sdk-transfer/lib/aws-sdk-transfer/types.rb', line 120
class As2ConnectorConfig < Struct.new( :local_profile_id, :partner_profile_id, :, :compression, :encryption_algorithm, :signing_algorithm, :mdn_signing_algorithm, :mdn_response, :basic_auth_secret_id) SENSITIVE = [] include Aws::Structure end


Know us! Who are we??
Best Delicious Pizza is the pizza shop that has been in pizza business in Kigali to day and offers a very unique atmosphere for customers in addition to home delivery services for all pizza orders and we know that pizza is a family meal which popular around the world and that has resulted in a large number of chains of pizza shops but what you have to know is that none of them are better and taster than our pizza in BDP.!!


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Welcome to the Fons Research Group Homepage!
This is the home page of the Fons research group of Keio University Faculty of Science and Technology Yagami Campus. Welcome. On these pages, you will find an introduction ot the current and some past research. I am interested in a variety of different topics and always interesting in learning more about new things.
I would like to create an international environment for students working with me. Both English and Japanese languages are welcome. I will try my best to give students a different perspective filled with international collaborations. Please join me in learning more about the world.
Paul Fons
PhD in Materials Science
University of Illinois at Urbana-Champaign
MS in Physics
University of Illinois at Urbana-Champaign
BSc in Physics
Bates College, Lewiston ME
Computational Materials Science
Use of Python-based APIs for ab-initio calculations and analysis
Understanding the structure of crystalline and amorphous materials
Responsibilities include:
Current Research Themes
There are several ongoing themes present in the Fons research group some of which are listed below. The basic theme is to understand atomic level structure and use the resulting understanding to optimize functionality. This includes the use of synchrotron radiation to investigate the physical and electronic structure of solids using tools such as x-ray absorption spectroscopy (XAFS) or high-energy photoemission spectroscopy. XAFS is a technique particular useful for understanding the structure of amorphous solids. Ultrafast dynamics has also been a topic of interest with collaborative efforts including using the free-electron laser SACLA at SPring-8, coherent phonon dynamics, or ab-initio molecular dynamics calculations.
*ab-initio calculations of material properties, structure, and dynamics.
Using lasers and x-rays to probe ultrafast dynamics.
Materials whose structure is used for storage.
Using synchrotron radiation to probe amorphous structure.
A complete list of (over 300) publications can be found at Google Scholar.


Health insurance is an insurance that covers the whole or a part of the risk of a person incurring medical expenses, spreading the risk over numerous persons. The amount insurance covers depends on the insurer and what the health provider accepts.
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Event Location:
ISEP
Rua Dr. António Bernardino de Almeida, 431
Porto, Porto, Portugal
Abstract:
In this session Peter Willmot (who has developed embedded/IoT and similar applications with SQL back-ends for many years) will help you to understand some of the opportunities that SQL (and, to a lesser extent, .Net) offer when you need to design and build effective, scalable and secure IoT back-end platforms with SQL Server. The session content covers various aspects of a typical SQL IoT back-end notably including: - working work binary-opaque data streams using SQL CLR - leveraging SQL Service Broker and Queues for CQRS and deferred aggregation scenarios - consistent JSON handling across SQL versions - selecting optimal data types and indexes for IoT-typical data structures
Speaker(s): Peter Willmot,
Abstract:
The modern connected world requires connected solutions, beyond basic relational engine - think about web pages connections, social media network communications or map path finding. Even though one can implement eventually everything with a relational engine, the bigger amount of analysed data is involved, the less probable is that your analysis will be done on time and with acceptable ease for the developers. Graph databases do exist in the wild since 1960s, but only in the last 2 decades - with the advances of the internet, started to conquer wider recognition and usage. Let's dive into this diverse world of graph databases and discover the new kid on the block - the GraphDB in SQL Server 2017 Azure SQL Database, which promises to allow you to expand and convert your workloads for solving modern connected world problems.
Speaker(s): Niko Neugebauer,
Abstract:
DevOps and continuous integration provide huge benefits to data warehouse development. However, most BI professionals have little exposure to the tools and techniques involved. John will be showing how you can use Visual Studio Team Services (VSTS) to build and test your data warehouse code and how to use Octopus Deploy to deploy everything to UAT and production. This is a demo heavy session which will introduce you to exactly how powerful DevOps can be in practice and will cover: * Setting up Visual Studio Team Services to act as your build server * How to use Octopus Deploy to deploy your entire data warehouse * Developing a build-centric PowerShell script with psake * Building and deploying SQL Server Data Tools projects with DAC Publish profiles * Writing and running automated unit tests * The many problems of automating tabular model deployments Please visit John's blog for practical tips on how to apply DevOps techniques to your Data Warehouse: https://devops-your-dwh.
Speaker(s): John Tunnicliffe,
Abstract:
dbachecks is a framework created by and for SQL Server pros who need to validate their environments. It is a free, open source module (created by dbatools team) that allows data pros to crowdsource our checklists using PowerShell's open source testing framework, Pester. We all share similar checklists and mostly just the server names and RPO/RTO/etc change. We offer over 80 built-in checks. Imagine being able to easily ensure that: - Backups are being performed within your policy - Identity columns are not about to max out - Database integrity checks are being performed and corruption does not exist - Disk space is not about to run out - SQL Servers are compliant with DISA, CIS, and more Do you already run your Pester checks? No problem, we can run your tests too. And to top it off, we make it easy to email yourself or view the results of your tests in a gorgeous Power BI Dashboard. Join us to see how easy (and beautiful) it can be validate all of your SQL Server environments!
Speaker(s): Cláudio Silva,
Abstract:
Docker has taken the world of IT by storm and looks to be ushering in the greatest platform paradigm shift since virtualisation and the public cloud. The transient nature of Docker containers makes them the perfect fit for spinning up and then tearing down SQL Server instances as part of continuous integration pipelines. Jenkins is the most popular build automation engine in the open source community, it has phenomenal plugin support, it is used by the likes of Netflix and eBay and excels in its ability to handle build pipelines as code. In this session you will learn how a simple build pipeline that takes a SQL Server data tools project checked out from source code control, built into a DACPAC which is then deployed to a SQL Server instance can be extended to use containers, multi-branch build pipelines, tSQt testing and much much more.
Speaker(s): Christopher Adkin,
Abstract:
Many of Open Knowledge International's projects are technical in nature. Its most prominent project, CKAN, is used by many of the world's governments to host open catalogues of data that their countries possess. CKAN is a tool for making open data websites. (Think of a content management system like WordPress – but for data, instead of pages and blog posts.) It helps you manage and publish collections of data. It is used by national and local governments, research institutions, and other organizations who collect a lot of data. In this talk I'll go over some use-cases of Open Knowledge Platform implementations by the Portuguese Government, the architectural features, the difficulties and different approaches to solve them.
Speaker(s): Pedro Sousa,
Abstract:
Can you use GEOGRAPHY data types to calculate and display celestial phenomena and does it make sense? It needs some math and the willingness to use SQL objects for purposes, they haven’t been designed for. This session is a (hopefully) entertaining exercise to combine scarcely used data types with a bit of astronomy and math to calculate and visualize the relationship between sun and wind turbines (i.e. moving shadows that may annoy the neighbors) solely by using SQL Management Studio. Only GEOGRAPHY data type will be used to show the richness and beauty of its functionality. Apart from 2-3 formulas everything will be handled in SQL.
Speaker(s): Arne Bartels,
Abstract:
By PASS Summit there will be enough news about vNext of the SQL Server and the already publicly announced improvements for the Columnstore Indexes such as Online Rebuild for the Clustered Columnstore Indexes Batch Mode for the Rowstore Indexes will be available for everyone to test and who knows, maybe even put into production. Join me in discovering all documented and non-documented features and how they will affect your On-Premises and Cloud Instances.
Speaker(s): Niko Neugebauer,
Abstract:
Azure Cosmos DB is Microsoft's globally distributed, multi-model database. This is NoSQL in the cloud. In this session, you'll see how to use it to create columnar tables, JSON documents and graphs, you'll understand what that means, see what's the difference with relational tables, and how it can be useful for you.
Speaker(s): Rudi Bruchez,
Abstract:
Agile BI promises to deliver value much quicker to its end users. But how do you keep track of versions and prioritize all the demands users have? With Visual Studio Online (cloud version of Team Foundation Server) it is possible to start for free with 5 users, with Version Control, Work Item management and much more. In my session you will get the directions to a quick start with Visual Studio Online. You will learn the possibilities of Version Control and in which way to implement Scrum work item management with all available tools.
Speaker(s): Sander van der hoeff,
Abstract:
In-Memory OLTP has come a long way since it was first introduced in SQL Server 2014. Many of the early restrictions have been lifted, but still fear and uncertainty of adoption into Production environments exists. In this session, we will explain and demonstrate when, how, and where you should use In-Memory OLTP to improve your SQL Server performance. We will discuss using it in real-world production scenarios, highlighting administrator best practices, and developer use cases and considerations.
Speaker(s): Mark Broadbent,
Abstract:
This session will cover the basics of dynamic SQL; how, why and when you may wish to use it with demos of use cases and scenarios where it can really save the day (trying to perform a search with a variable number of optional search terms, anyone?). We will also cover the performance and security impacts touching on the effect on query plans, index usage and security (SQL injection!) along with some best practices.
Speaker(s): Joanna Wolthuis,
Abstract:
Power BI is an amazing BI platform out of the box, but there' is a lot of things that you can do with Power BI that probably you dont even imagine! Come to my session to find out....
Speaker(s): Rui Romano,
Abstract:
The concurrency model of most Relational Database Systems are defined by the ACID properties but as they aim for ever increasing transactional throughput, those rules are bent, ignored, or even broken. In this session, we will investigate how SQL Server implements transactional durability in order to understand how Delayed Durability bends the rules to remove transactional bottlenecks and achieve improved throughput. We will take a look at how this can be used to compliment In-Memory OLTP performance, and how it might impact or compromise other things. Attend this session and you will be assimilated!
Speaker(s): Mark Broadbent,
Abstract:
I find performance tuning to be one of the most challenging and interesting tasks as a DBA. In a session based on demonstrations, I'll show some real live performance issues and give tips that will boost performance from 4 to 100 times! Examples will cover both application queries and maintenance tasks and I'm sure you'll like it :-)
Speaker(s): Etienne Lopes,
Abstract:
Stream Analytics is the solution from Microsoft for event based data processing on Azure. The objective of this session is to show the value of real-time data insights with a fictional Car Racing Simulator, detailing the steps from the events source, until the analysis of the race telemetry.
Speaker(s): Murilo Miranda,
Abstract:
Service Broker is one of that features that every DBA knows that exists but just few of them uses, and these feature is awesome for some use cases. In this session I will show you where Service Broker can be very useful, how to configure and to solve the common errors.
Speaker(s): Ivan Campos,
This is a list of speakers from the XML Guidebook records. The details and URLs were valid at the time of the event.
LinkedIn: https://pt.linkedin.com/in/idcampos
Contact: http://wizarddba.com/
Ivan Campos is currently a database administrator in 3C Payment a fin-tech in Luxembourg. (3CPayment.com). He is Microsoft Most Valuable Professional, active speaker at local community meetings in Portugal and outside Portugal. He is the leader and one of the founders of the community based in the north of Portugal Porto.Data (www.portodata.net) and the organizer of SQLSaturday in Porto Portugal.
LinkedIn: https://pt.linkedin.com/in/claudioessilva
Contact: http://claudioessilva.eu
Cláudio works as SQL Server DBA and he is an former PowerShell MVP who loves to automate any process that needs to be done more than a couple of times. He is an active member on the PowerShell and SQL communities. He contributes to dbatools project (https://dbatools.io) and is always available to help. You can find him on slack and twitter platforms. He also helps on some Portuguese in-person events such as SQLSaturday Lisbon and TugaIT. He is also a regular speaker on these and other events.
LinkedIn: http://www.linkedin.com/in/drjohntunnicliffe
Contact: https://devops-your-dwh.com/
Dr John Tunnicliffe is a well-respected designer and architect of business intelligence solutions who likes nothing more than getting his hands dirty with real life coding problems. John is a recognised expert in applying continuous integration techniques to data warehouse projects, thereby ensuring code is automatically built, deployed and tested as changes are made by the development team. As a regular speaker at the SQLBits conference and PASS SQL Saturday events, John has covered topics such as building an infrastructure to support real-time OLAP and continuous integration and the data warehouse.
LinkedIn: https://pt.linkedin.com/in/pmsousa
Contact: http://www.devscope.net
Pedro Sousa lives in Porto, Portugal and he currently works as a Senior IT Operations Analyst at Basecone. Started working with SQL Server at version 6.5 and although DBA is not his primary role, always had a particular interest for it. Nowadays one of his main focus is Microsoft Azure and integration with on-premises networks, working from the copper wire to the Cloud.
LinkedIn: http://www.linkedin.com/in/retracement
Contact: http://tenbulls.co.uk
Mark Broadbent is a Data Platform MVP and SQL Server MCM with more than 20 years of experience working with SQL Server and principal of SQLCloud, a consultancy specializing in concurrency control and highly available solutions. He is the founder of the UK's SQLSaturday Cambridge (its first and largest), SharePoint Saturday Cambridge, the Hybrid Virtual Chapter and the East Anglia SQL User Group.
LinkedIn: https://fr.linkedin.com/in/rudibruchez
Contact: http://www.babaluga.com/
(same as before)
LinkedIn: http://pt.linkedin.com/in/murilomiranda/
Murilo Miranda is a blogger, speaker and SQL Server MVP from Portugal. Nowadays he#39;s a Cloud Operations Engineer at DataStax. Murilo’s passion for working with people coupled with his honesty have helped him establish effective, meaningful relationships with his clients. When he isn’t working, he can be found enjoying life with his family, watching football and playing Playstation.
LinkedIn: http://nl.linkedin.com/in/shoeff
Contact: http://www.du-sabot.nl
With over 20 years of experience in automation Sander van der Hoeff knows his way around in the ICT business. Since 2000 Sander is Specialized in business intelligence and data warehousing using the full SQLServer Stack. In 2012 Sander founded his own BI-company: Du Sabot. Nowadays Sander spends his time on several BI- and DWH-projects as an independent professional. Sander combines deep technical knowledge with the capability to explain difficult BI- and DWH-concepts to the non-technical people
Contact: https://sqland.wordpress.com
Etienne Lopes currently works as a SQL Server DBA at Celfinet. Working with SQL Server since 1997, member of sqlport community (www.sqlport.com), regular speaker since 2012 at SQL Server events such as: SQL Saturday and 24 Hours of Pass. Blog: http://sqland.wordpress.com/
Peter has been writing software (and teaching folk how to write software) for over 30 years. He has worked with SQL Server as an architect and developer for more than 20 years (since SQL 4.2) and has also worked extensively with the .Net and various other development platforms. Peter is a past MSDN Regional Director and was also an MVP (SQL Server and Architecture) for many years. He is a passionate and regular speaker and various industry events around the world.
LinkedIn: https://pt.linkedin.com/in/ruiromano
Contact: http://ruiromanoblog.wordpress.com/
Rui Romano lives in Portugal and he leads the Business Intelligence team at DevScope. He has been Developing amp; Architecting software solutions since 2003 always focused in the Business Intelligence area.
LinkedIn: https://www.linkedin.com/in/joannawolthuis/
Joanna Wolthuis is an independent contractor specialising in T-SQL database development and reporting using SSRS and Excel based solutions for the last 8 years. She is passionate about data and learning everything about anything. Aside from SQL Joanna enjoys traveling, nice food and attempting to be an acrobat (not at the same time!).
LinkedIn: http://pt.linkedin.com/in/webcaravela/
Contact: http://www.nikoport.com
Niko Neugebauer is a Data Platform Consultant. A SQL Server MVP with over 20 years of experience in IT, he is passionate about the Microsoft Data Platform and community. Founder of the Portuguese SQL Server User Group and the main organizer of the first SQLSaturday event outside of North America (#78 Portugal), Niko speaks regularly at events such as PASS Summit, SQLRally, SQLBits, and SQLSaturday events around the world. Niko loves sharing information and knowledge and has authored over 130 blog posts on Columnstore Indexes, and regularly contributes to the open-sourced CISL library focused on Columnstore Indexes.
LinkedIn: https://www.linkedin.com/profile/view?id=207669359amp;trk=nav_responsive_tab_profile
Master of physic in Germany 2000, worked as MS Flightsimulator Expert on the side. Employed at OLTEC Windamp;Solar as C++/Web/PHP/MySQL -Programmer. Company bought by Vestas 2004 shifting to MS-SQL,SSIS until now.
LinkedIn: http://pt.linkedin.com/in/webcaravela/
Contact: http://www.nikoport.com
Niko Neugebauer is a Data Platform Consultant. A SQL Server MVP with over 20 years of experience in IT, he is passionate about the Microsoft Data Platform and community. Founder of the Portuguese SQL Server User Group and the main organizer of the first SQLSaturday event outside of North America (#78 Portugal), Niko speaks regularly at events such as PASS Summit, SQLRally, SQLBits, and SQLSaturday events around the world. Niko loves sharing information and knowledge and has authored over 130 blog posts on Columnstore Indexes, and regularly contributes to the open-sourced CISL library focused on Columnstore Indexes.
LinkedIn: http://www.linkedin.com/in/retracement
Contact: http://tenbulls.co.uk
Mark Broadbent is a Data Platform MVP and SQL Server MCM with more than 20 years of experience working with SQL Server and principal of SQLCloud, a consultancy specializing in concurrency control and highly available solutions. He is the founder of the UK's SQLSaturday Cambridge (its first and largest), SharePoint Saturday Cambridge, the Hybrid Virtual Chapter and the East Anglia SQL User Group.
LinkedIn: https://www.linkedin.com/in/wollatondba
Contact: http://www.chrisadkin.io
Chris is a freelance SQL consultant who has been working with SQL Server since 2000, his passion is for squeezing every last drop of performance out of SQL Server and understanding the database engine at a level which conventional tools cannot provide any insights on.
The following is a list of sponsors that helped fund the event.


2 Corinthians 3:13
And not as Moses, which put a vail over his face, that the children of Israel could not stedfastly look to the end of that which is abolished:


Geolocation Plugin Demo
Get current position (once)
Start watching position (continuous)
Stop watching position
Map
Your distance from major cities
All position data


In pictures: the Tezgam tragedy
01 Nov 2019, 10:21 by AFP
Funerals began at dawn in Pakistan on November 1 after a devastating fire ripped through a crowded train carrying religious pilgrims, killing at least 74, with many of the victims resident of one southern town.
The burnt-out train carriages a day after the passenger train caught on fire in Rahim Yar Khan. PHOTO: AFP
Inside of a burnt-out train carriage a day after the passenger train caught on fire in Rahim Yar Khan. PHOTO: AFP
People look at the burnt-out train carriages. PHOTO: AFP
People look at the burnt-out train carriages. PHOTO: AFP
People walk past the burnt-out train carriages. PHOYO: AFP
A man looks at the burnt-out train carriages. PHOTO: AFP
The burnt-out train carriages a day after a passenger train caught on fire in Rahim Yar Khan. PHOTO: AFP
People look at the burnt-out train carriages. PHOTO: AFP
The burnt-out train carriages a day after a passenger train caught on fire in Rahim Yar Khan. PHOTO: AFP
The burnt-out train carriages a day after a passenger train caught on fire in Rahim Yar Khan. PHOTO: AFP


Reports on the OHCHR Investigation on Sri Lanka.
Recommendations and Conclusions.
Principle Findings
Report 2016
Violations and deprivations of liberty .
Report Enforced Disappearances .
Resolution adopted by HRC.


ParSeq JSON Trace Viewer
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--- title: 4th & 5th Grade Summer Camps layout: default ---
Back to main Summer Camp page
Click the panels below for information about each camp.
Partner Camp with Natural History Museum of Utah, Utah’s Hogle Zoo, This Is the Place Heritage Park, & Camp Kostopolous
If you attend only one camp this summer make it this one! Spend the week at a different camp location each day and participate in an awesome mix of signature summer camp activities. Climb ropes courses, ride horses, and fish at Camp Kostopulos. Investigate Utah’s history through train rides, gold panning, and pioneer activities at This is the Place Heritage Park. Discover the animal kingdom, study unique animal adaptations, and observe a plethora of critters at Utah’s Hogle Zoo. Go on a botanical adventure and explore the world of plants, hike the foothills of Utah, and uncover the wonders of the natural world at Red Butte Garden. Finally, connect with your inner scientist as you concoct chemical potions, have fun with physics, and more at the Natural History Museum of Utah. Don’t miss out on this all-day, all-week adventure!
Click Here for Camp Overview.
NOTE: Registration for this class is done through NHMU
Shelli Campbell, NHMU Camp Director,<PHONE_NUMBER>
Choose from one session below. Each session indicates where your camper will need to be dropped off and picked up each day.
Session A:
Monday-NHMU
Tuesday-This is the Place
Wednesday-Camp Kostopulos
Thursday-Utah's Hogle Zoo
Friday-Red Butte Garden
Session B:
Monday-This is the Place
Tuesday-Camp Kostopulos
Wednesday-Utah's Hogle Zoo
Thursday-Red Butte Garden
Friday-NHMU
Session C:
Monday-Camp Kostopulos
Tuesday-Utah's Hogle Zoo
Wednesday-Red Butte Garden
Thursday-NHMU
Friday-This is the Place
Session D:
Monday-Utah's Hogle Zoo
Tuesday-Red Butte Garden
Wednesday-NHMU
Thursday-This is the Place
Friday-Camp Kostopulos
Session E:
Monday-Red Butte Garden
Tuesday-NHMU
Wednesday-This is the Place
Thursday-Camp Kostopulos
Friday-Utah's Hogle Zoo
Red Butte Garden / Several Other Locations
Members: $292.50, Public: $325
Shelli Campbell, NHMU Camp Director,<PHONE_NUMBER>
Partner Camp with Natural History Museum of Utah (NHMU)
Partner Camp with Natural History Museum of Utah (NMHU) Get ready to explore the natural world with Red Butte Garden and the Natural History Museum of Utah! Spend your mornings at NHMU investigating animals, insects, and water and soil science through hands-on projects, experiments, and excursions in the foothills around the Museum. In the afternoon, travel to Red Butte Garden to discover food chains and trophic levels, as you create exploding photosynthesis art, dissect owl pellets, and more.
Drop off at NHMU by 8:30AM and pick up at Red Butte Garden by 4PM
Click Here for Camp Overview.
NOTE: Registration for this class is done through NHMU
Shelli Campbell, NHMU Camp Director,<PHONE_NUMBER>
Red Butte Garden / Natural History Museum of Utah 301 Wakara Way, Salt Lake City, UT 84108
Members: $261, Public: $290
801-585-3948
* Short week due to Independence Day and Pioneer Day holidays.


--- layout: page title: A Framework for Graph Database Applications date: 2015-07-30 22:22:13.000000000 -04:00 type: page parent_id: '' published: true status: publish categories: [] tags: [] meta: {} author: ---
The XN Framework is quickly becoming the go-to tool for rapidly producing graph database applications. In this world of Agile and NoSQL backed schema-less application development it isn't enough to just be fast, you need to ensure that the code your team produces is testable and maintainable from day one. We built the XN Framework just for you, with a perfect blend of enterprise-grade features and state-of-the-art technology.
While building the XN Logic framework, we've worked with Neo4j, OrientDB, and Sparksee graph databases and understand their unique pros and cons. We also understand where a key-value store, a document store, or a relational database might be a complimentary fit for your requirements and we know how to tie your graph database to them. You can achieve all of this cleanly with our proven toolset.
Typically APIs are very static, and they often require re-programming. The XN Framework API is extensible, allowing you to build out URLs in any valid way because of its ability to retain context. So, with any standard requests already in the system, this means you can just keep adding requests in an existing context. As a result, you save time building on the existing things that teams typically spend time on, freeing you up to do more sophisticated tasks that add the most value to your business.
XN Logic’s framework includes the HistoryGraph which lets you run ad-hoc queries on your system in real-time to generate a comprehensive analysis of that system at any point of its existence. Usually that kind of information is static—dumped to a record—and requires pre-processing, plus the involvement of other people. The HistoryGraph eliminates that and is non-resource-intensive.
Getting an XN Logic application up and running from design through to deployment can take as little as one week.
Don't just take our word for it though, setup a proof-of-concept today!


My header
Related Pages
Here is a list of all related documentation pages:
Introduction
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{% extends "base.html" %} {% load static %} {% block site_style %} {{ block.super }} {% endblock site_style %} {% block body_class %}home{% endblock body_class %} {% block layout %}landing{% endblock layout %} {% block content %}
This free, online decision support tool helps forest and stream restoration practitioners support salmon recovery across North Central Washington. The easy-to-use website informs salmon recovery by assessing the effects of forest restoration activity on snowpack retention and subsequent water supply and timing.
Water availability, especially during the late summer, affects salmon populations in the Upper Columbia. One of several approaches to increasing the amount of water available for instream flow in the late summer is by increasing the capture and duration of storage of mountain snowpack. This tool, developed by Ecotrust, builds on Pacific Northwest National Laboratory’s Distributed Hydrology Soil Vegetation model (DHSVM) and forest research by Pacific Northwest Research Station to identify both how forest restoration activity affects downstream flows, and where to target upstream restoration activities to benefit specific in-stream locations.
The goal of Snow2Flow is to simulate the approximate change in streamflow with realistic forest treatments. These treatments were developed in collaboration with Okanogan-Wenatchee National Forest (OWNF) managers. While these four treatments do not exactly reflect every scenario OWNF managers will use, the goal was to match them as broadly as possible. Results are not meant to predict exact changes in streamflow, since actual changes will vary based on the weather of the post-treatment years. Furthermore, this tool is not designed to guide OWNF forest management, but rather explore how planned forest management may effect streamflow. Our hope is this model can be used to identify where forest management can potentially increase streamflow and improve salmon habitat.


[ MINDSET ] › indifferent
[ SETTING ] › home
My entire journey with brugmansia was not to get high, or to trip, but to enlighten myself & others. One should never try anything without knowing the possible outcomes.
Furthermore, this was my first time using brugmansia. As an avid tripper I made the decision to try it without a sitter. This could have turned out terribly bad, but luckily it didn't. I actually enjoyed most of the experience. It really changes the way I think. What's so dangerous about brugmansia & datura is that thought process gets jumbled and I think that I'm thinking normally. Let me tell you.. I wasn't, by any means.
Now for the goodies:
[ PREPARATION ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
6 brugmansia leafs (all mature, about 7' X 15' each)
5 paper coffee filters (they get clogged by this mixture and you have to switch them out)
1 brugmansia blossom (mature, pink)
1 milk jug
1 large cup (that won't melt with boiling water added)
1 pot for heating the mixture
1 cup of sugar
1 funnel
• cut the plant-matter into shreads with a pair of scissors
• put .125 gallons of water (fill to that bottom line on a milk jug) in the pot on the stove.
• turn the stove on high until the water is about to boil, then lower the heat to prevent boiling
• then add the shredded plant-matter which should cook for approximately 20-25 minutes
• this mixture will now be strained this through a few coffee filters into the cup
• when finished straining the liquid put all of the pulp into a filter (this may take 2 filters) into the cup
• using the funnel, pour a cup of sugar into the milk jug
• pour the mixture from the cup back into the pot and turn the heat on again, but don't boil it; just get it really hot
• using the funnel, pour the heated liquid into the milk jug, cap the jug, shake it up
• you will need to release the pressure a few times during this process (remove the cap)
• let this substance cool down naturally (don't put it in your refridgerator or icebox)
[ DOSAGE ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
I had less than half of the mixture above, and it made me hallucinate pretty decently, but as you read, took a while to kick in.
[ FRIDAY, SEP 30, 2005 ] › [ 21:45 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
Drank 1 coffee-cup mug of tea (approximately .75 cups)
[ FRIDAY, SEP 30, 2005 ] › [ 21:58 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
I can tell that I'm not sober, but the effects are not very strong as of this moment. Feeling as though my eyes are trying to look in two different directions, but only in slight proportions. Cottonmouth is starting to take effect as well, but once again, only slightly.
[ FRIDAY, SEP 30, 2005 ] › [ 22:04 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
My sense of balance seems slightly distorted. I am not quite stumbling, but am uncertain as to whether or not I would be able to walk a straight line. I am noticing that I do not feel the 'heavy' feeling that I have read about.
[ FRIDAY, SEP 30, 2005 ] › [ 22:05 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
I am planning to drink another cup @ 22:45 if I feel it necessary.
[ FRIDAY, SEP 30, 2005 ] › [ 22:08 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
Heartrate is increased, and it feels as though my pupils are dilating. They don't appear to be dilated (I just checked) but instead of feeling heavy, I am beginning to feel light.
[ FRIDAY, SEP 30, 2005 ] › [ 22:16 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
My pupils are beginning to dilate... Or at least appear to be.
[ FRIDAY, SEP 30, 2005 ] › [ 22:19 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
I am beginning to feel tired. I was expecting this. I am going to fight sleep, at least long enough to drink another cup of this wonderul (so far) tea. Also, cottonmouth is beating me with a whip right now. It feels like I hung my opened-mouth window out the car window on a 200 mile journey; in other words.. It's DRY AS HELL!
[ FRIDAY, SEP 30, 2005 ] › [ 22:33 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
I just used the restroom and found that my urine didn't flow as freely as it normally would. I had to force my urine out, which made me paranoid b/c I have read that many people have urinated & defecated on themselves without even knowing it while on this trip & boy was I straining! Luckily, I walked away clean.
[ FRIDAY, SEP 30, 2005 ] › [ 22:39 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
I drank most of another cup of the tea (coffee-cup mug = .75 cup)
[ FRIDAY, SEP 30, 2005 ] › [ 22:45 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
It's been 1 hour since I first consumed the tea. I am now seeing odd hallucinations. There is a face that's multicolored coming from the corner of my room, it just comes out of the shadow for a second, then returns.  The face is black for the most part, as if its face were see-thru, but its facial features are neon lights. There are waves of green & yellow illuminations flowing across my cieling. The patterns beneath (higher than) the coloring look like doily patterns that are morphing and whatnot. The walls look as if someone splattered little pink, green, & blue drops all over them.
[ FRIDAY, SEP 30, 2005 ] › [ 22:47 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
I am beginning to feel a little sleepy, but restless at the same time. No jitters and no 'out of the ordinary' visuals. By out of the ordinary I mean things that I see anyway. I have visuals all the time, even sober. I remember saying as a teen that it would be 'cool' to hallucinate all the time as if I were on acid. I still love the hallucinations, but they can get annoying. Remember that bit of information. It does get annoying, not all the time, but it does. Especially the auditory hallucinations. I hear people whispering, but can't find them. I hear people call my name, but they're nowhere to befound. If you had that happen constantly, I am sure you would find it annoying as well.
[ FRIDAY, SEP 30, 2005 ] › [ 22:51 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
I finished off the cup of tea that I began drinking @ 22:39. I have now consumed 1.5 cups of liquid brugmansia.
[ FRIDAY, SEP 30, 2005 ] › [ 23:22 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
I took a shower and I noticed a few strange things. On the way to the shower from my room I noticed that my equilibrium was off-balanced, though I was thinking what I thought to be clearly. I could see myself walking all drunk-like, yet I felt mentally sober; much like ether. Once I was in the shower there was a folded & twisted washcloth...  This eye wouldn't quit making eye contact with me. I was shocked at first when I saw it, and I jumped. I don't usually jump even if I'm scared to death. I don't know what made me jump - it was merely a washcloth. I knew this because I noticed it before it became an eyeball & ripped flesh.
The second oddity that I noticed is that one of the screws holding the shower crown in (the board running along the walls at the ceiling) grew legs and started 'sniffing' around the shower. It appeared to be a spider, but when I got closer to take a look, the legs dissipated; they faded out until the were gone. And there... Was the screw.. In all of its glory.
Another strange thing is that my hands were red in the shower.. Actually - they're still red. They look as though one would if they took a large dose of niacin. Also, where the shower wall meets the floor there is some writing, but it's hard to read, and when I get closer it fades away. I managed to read part of this; which reads, 'you are not...' I have no idea as to the meaning of this.
Even though I have never been afraid of the dark I was on brugmansia. I wasn't like so scared that I wouldn't walk into the dark, but I was really nervous about doing so. I've eaten 27 hits of acid before (alice-in-wonderland) and went to a dark room intentionally to really get my mind ticking. The people I was with (also veteran trippers) only took 4 hits each, and wigged out.
The reason I'm telling you this is because I don't scare easy, even when tripping extremely hard. This mystical plant made me nervous about walking in the dark, who knows what it may do to you. I suggest avoiding dark rooms all-together.
[ SATURDAY, OCT 01, 2005 ] › [ 00:13 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
I laid back on my bed and watched all sorts of things fly by. These hallucinations are unlike any that I've had. On acid, the visuals are smooth and constant. With brugmansia, they don't move quite as often, but when they do... They snap into place. Small things do move smoothly on brugmansia, but they move so fast I don't really get a good look at them. Everything is breathing, but not as much as I would have expected. My chest-of-drawers is trying to walk away right now, but the carpet's grip is too strong.. I know this isn't really happning, but it's quite amusing to watch.
[ SATURDAY, OCT 01, 2005 ] › [ 08:11 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
Well, I went to sleep, with some difficulty in lieu of the fact that I couldn't get comfortable. I was starting to worry myself that perhaps I took too much b/c all of a sudden I was feeling VERY strange; completely out of place. But I have awakened, and I am still tripping. Not quite as hard, but still am. I had an awful taste in my mouth so I brushed my teeth. My stomach was feeling a little queezy so I have eaten a bowl of cereal.
[ SATURDAY, OCT 01, 2005 ] › [ 11:00 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
Yep, still tripping; and there appears to be smoke coming from my desk. The smoke keeps flying by my face, and I say to myself 'oh yea, I need to smoke that cigarette before it's dead' but when I reach down to grab it... I realize that I don't even have an ashtray in here right now, let alone a burning cigarette. I've already done this several times today. My pupils are still pretty dilated, and the cottonmouth is still present, but not very bad.
I just looked out my bedroom door b/c of the music and I wanted to know who was messing with my stereo. I'm the only one here, so my radio shouldn't have changed stations. When I opened my door there stood sherlock holmes. Such and odd person to see; from all of my research you tend to run into people you used to know and such. I've never met Mr. Holmes.. But he's been to my house now. By the way... There wasn't any music playing to start with. As I am typing this out, my door is attempting to close itself, but I have it propped open with my shoes. I think my door might be getting mad b/c it's breathing heavily now. No, I do not actually think my door is mad, I know it's only a hallucination.
[ SATURDAY, OCT 01, 2005 ] › [ 11:37 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
Trippin' like a villian. This text is turning shades of grey, red, orange, yellow, blue, & violet, but only certain words. The problem is, I can't tell which ones are highlighted by color b/c they keep changing; the color seems to be playing musical chairs with the music that isn't playing, but's ok.. I hear the music too. I know it's not on, but I hear it nonetheless. I am unable to read anything unless I hold it at arm's length. When I try to read small print (having to hold it closer) my eyes don't seem to want to point in the same direction; much like astigmatism.
[ SATURDAY, OCT 01, 2005 ] › [ 12:30 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
Still tripping. I am semi-watching a spider build a spider web across the bottom of my monitor. The reason I say 'semi-watching' is b/c if I look directly at her or her web.. It disappears.
I am going to go ahead and post this. The trip is still going steady; though I feel much more comfortable now. I hope this gives some people some insight as to the effects of this mystical plant. Ok...
[ SATURDAY, OCT 01, 2005 ] › [ 12:40 ]
+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+
Something under my bed just growled. It was quite a sinister growl. I know it's only in my head, so I am going to ignore it... Also a penny just came out from behind my monitor and landed on top of it, but without sound. Sneaky pennies. My walls look as thought they're being projected onto a backdrop and the wind is blowing it around. And they're assuming a pink-red color.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Web UI
Apache Spark provides a suite of web user interfaces (UIs) that you can use to monitor the status and resource consumption of your Spark cluster.
Table of Contents
- Jobs Tab
- Stages Tab
- Storage Tab
- Environment Tab
- Executors Tab
- SQL Tab
- Structured Streaming Tab
- Streaming (DStreams) Tab
- JDBC/ODBC Server Tab
Jobs Tab
The Jobs tab displays a summary page of all jobs in the Spark application and a details page for each job. The summary page shows high-level information, such as the status, duration, and progress of all jobs and the overall event timeline. When you click on a job on the summary page, you see the details page for that job. The details page further shows the event timeline, DAG visualization, and all stages of the job.
The information that is displayed in this section is
- User: Current Spark user
- Total uptime: Time since Spark application started
- Scheduling mode: See job scheduling
- Number of jobs per status: Active, Completed, Failed
- Event timeline: Displays in chronological order the events related to the executors (added, removed) and the jobs
- Details of jobs grouped by status: Displays detailed information of the jobs including Job ID, description (with a link to detailed job page), submitted time, duration, stages summary and tasks progress bar
When you click on a specific job, you can see the detailed information of this job.
Jobs detail
This page displays the details of a specific job identified by its job ID.
- Job Status: (running, succeeded, failed)
- Number of stages per status (active, pending, completed, skipped, failed)
- Associated SQL Query: Link to the sql tab for this job
- Event timeline: Displays in chronological order the events related to the executors (added, removed) and the stages of the job
- DAG visualization: Visual representation of the directed acyclic graph of this job where vertices represent the RDDs or DataFrames and the edges represent an operation to be applied on RDD.
- An example of DAG visualization for
sc.parallelize(1 to 100).toDF.count()
- List of stages (grouped by state active, pending, completed, skipped, and failed)
- Stage ID
- Description of the stage
- Submitted timestamp
- Duration of the stage
- Tasks progress bar
- Input: Bytes read from storage in this stage
- Output: Bytes written in storage in this stage
- Shuffle read: Total shuffle bytes and records read, includes both data read locally and data read from remote executors
- Shuffle write: Bytes and records written to disk in order to be read by a shuffle in a future stage
Stages Tab
The Stages tab displays a summary page that shows the current state of all stages of all jobs in the Spark application.
At the beginning of the page is the summary with the count of all stages by status (active, pending, completed, skipped, and failed)
In Fair scheduling mode there is a table that displays pools properties
After that are the details of stages per status (active, pending, completed, skipped, failed). In active stages, it’s possible to kill the stage with the kill link. Only in failed stages, failure reason is shown. Task detail can be accessed by clicking on the description.
Stage detail
The stage detail page begins with information like total time across all tasks, Locality level summary, Shuffle Read Size / Records and Associated Job IDs.
There is also a visual representation of the directed acyclic graph (DAG) of this stage, where vertices represent the RDDs or DataFrames and the edges represent an operation to be applied. Nodes are grouped by operation scope in the DAG visualization and labelled with the operation scope name (BatchScan, WholeStageCodegen, Exchange, etc). Notably, Whole Stage Code Generation operations are also annotated with the code generation id. For stages belonging to Spark DataFrame or SQL execution, this allows to cross-reference Stage execution details to the relevant details in the Web-UI SQL Tab page where SQL plan graphs and execution plans are reported.
Summary metrics for all task are represented in a table and in a timeline.
- Tasks deserialization time
- Duration of tasks.

- Result serialization time is the time spent serializing the task result on an executor before sending it back to the driver.
- Getting result time is the time that the driver spends fetching task results from workers.
- Scheduler delay is the time the task waits to be scheduled for execution.
- Peak execution memory is the maximum memory used by the internal data structures created during shuffles, aggregations and joins.
- Shuffle Read Size / Records. Total shuffle bytes read, includes both data read locally and data read from remote executors.
- Shuffle Read Fetch Wait Time is the time that tasks spent blocked waiting for shuffle data to be read from remote machines.
- Shuffle Remote Reads is the total shuffle bytes read from remote executors.
- Shuffle Write Time is the time that tasks spent writing shuffle data.
- Shuffle spill (memory) is the size of the deserialized form of the shuffled data in memory.
- Shuffle spill (disk) is the size of the serialized form of the data on disk.
Aggregated metrics by executor show the same information aggregated by executor.
Accumulators are a type of shared variables. It provides a mutable variable that can be updated inside of a variety of transformations. It is possible to create accumulators with and without name, but only named accumulators are displayed.
Tasks details basically includes the same information as in the summary section but detailed by task. It also includes links to review the logs and the task attempt number if it fails for any reason. If there are named accumulators, here it is possible to see the accumulator value at the end of each task.
Storage Tab
The Storage tab displays the persisted RDDs and DataFrames, if any, in the application. The summary page shows the storage levels, sizes and partitions of all RDDs, and the details page shows the sizes and using executors for all partitions in an RDD or DataFrame.
After running the above example, we can find two RDDs listed in the Storage tab. Basic information like storage level, number of partitions and memory overhead are provided. Note that the newly persisted RDDs or DataFrames are not shown in the tab before they are materialized. To monitor a specific RDD or DataFrame, make sure an action operation has been triggered.
You can click the RDD name ‘rdd’ for obtaining the details of data persistence, such as the data distribution on the cluster.
Environment Tab
The Environment tab displays the values for the different environment and configuration variables, including JVM, Spark, and system properties.
This environment page has five parts. It is a useful place to check whether your properties have been set correctly. The first part ‘Runtime Information’ simply contains the runtime properties like versions of Java and Scala. The second part ‘Spark Properties’ lists the application properties like ‘spark.app.name’ and ‘spark.driver.memory’.
Clicking the ‘Hadoop Properties’ link displays properties relative to Hadoop and YARN. Note that properties like ‘spark.hadoop.*’ are shown not in this part but in ‘Spark Properties’.
‘System Properties’ shows more details about the JVM.
The last part ‘Classpath Entries’ lists the classes loaded from different sources, which is very useful to resolve class conflicts.
Executors Tab
The Executors tab displays summary information about the executors that were created for the application, including memory and disk usage and task and shuffle information. The Storage Memory column shows the amount of memory used and reserved for caching data.
The Executors tab provides not only resource information (amount of memory, disk, and cores used by each executor) but also performance information (GC time and shuffle information).
Clicking the ‘stderr’ link of executor 0 displays detailed standard error log in its console.
Clicking the ‘Thread Dump’ link of executor 0 displays the thread dump of JVM on executor 0, which is pretty useful for performance analysis.
SQL Tab
If the application executes Spark SQL queries, the SQL tab displays information, such as the duration, jobs, and physical and logical plans for the queries. Here we include a basic example to illustrate this tab:
Now the above three dataframe/SQL operators are shown in the list. If we click the ‘show at <console>: 24’ link of the last query, we will see the DAG and details of the query execution.
The query details page displays information about the query execution time, its duration, the list of associated jobs, and the query execution DAG. The first block ‘WholeStageCodegen (1)’ compiles multiple operators (‘LocalTableScan’ and ‘HashAggregate’) together into a single Java function to improve performance, and metrics like number of rows and spill size are listed in the block. The annotation ‘(1)’ in the block name is the code generation id. The second block ‘Exchange’ shows the metrics on the shuffle exchange, including number of written shuffle records, total data size, etc.
Clicking the ‘Details’ link on the bottom displays the logical plans and the physical plan, which illustrate how Spark parses, analyzes, optimizes and performs the query. Steps in the physical plan subject to whole stage code generation optimization, are prefixed by a star followed by the code generation id, for example: ‘*(1) LocalTableScan’
SQL metrics
The metrics of SQL operators are shown in the block of physical operators. The SQL metrics can be useful when we want to dive into the execution details of each operator. For example, “number of output rows” can answer how many rows are output after a Filter operator, “shuffle bytes written total” in an Exchange operator shows the number of bytes written by a shuffle.
Here is the list of SQL metrics:
| SQL metrics | Meaning | Operators |
|---|---|---|
number of output rows | the number of output rows of the operator | Aggregate operators, Join operators, Sample, Range, Scan operators, Filter, etc. |
data size | the size of broadcast/shuffled/collected data of the operator | BroadcastExchange, ShuffleExchange, Subquery |
time to collect | the time spent on collecting data | BroadcastExchange, Subquery |
scan time | the time spent on scanning data | ColumnarBatchScan, FileSourceScan |
metadata time | the time spent on getting metadata like number of partitions, number of files | FileSourceScan |
shuffle bytes written | the number of bytes written | CollectLimit, TakeOrderedAndProject, ShuffleExchange |
shuffle records written | the number of records written | CollectLimit, TakeOrderedAndProject, ShuffleExchange |
shuffle write time | the time spent on shuffle writing | CollectLimit, TakeOrderedAndProject, ShuffleExchange |
remote blocks read | the number of blocks read remotely | CollectLimit, TakeOrderedAndProject, ShuffleExchange |
remote bytes read | the number of bytes read remotely | CollectLimit, TakeOrderedAndProject, ShuffleExchange |
remote bytes read to disk | the number of bytes read from remote to local disk | CollectLimit, TakeOrderedAndProject, ShuffleExchange |
local blocks read | the number of blocks read locally | CollectLimit, TakeOrderedAndProject, ShuffleExchange |
local bytes read | the number of bytes read locally | CollectLimit, TakeOrderedAndProject, ShuffleExchange |
fetch wait time | the time spent on fetching data (local and remote) | CollectLimit, TakeOrderedAndProject, ShuffleExchange |
records read | the number of read records | CollectLimit, TakeOrderedAndProject, ShuffleExchange |
sort time | the time spent on sorting | Sort |
peak memory | the peak memory usage in the operator | Sort, HashAggregate |
spill size | number of bytes spilled to disk from memory in the operator | Sort, HashAggregate |
time in aggregation build | the time spent on aggregation | HashAggregate, ObjectHashAggregate |
avg hash probe bucket list iters | the average bucket list iterations per lookup during aggregation | HashAggregate |
data size of build side | the size of built hash map | ShuffledHashJoin |
time to build hash map | the time spent on building hash map | ShuffledHashJoin |
task commit time | the time spent on committing the output of a task after the writes succeed | any write operation on a file-based table |
job commit time | the time spent on committing the output of a job after the writes succeed | any write operation on a file-based table |
Structured Streaming Tab
When running Structured Streaming jobs in micro-batch mode, a Structured Streaming tab will be available on the Web UI. The overview page displays some brief statistics for running and completed queries. Also, you can check the latest exception of a failed query. For detailed statistics, please click a “run id” in the tables.
The statistics page displays some useful metrics for insight into the status of your streaming queries. Currently, it contains the following metrics.
- Input Rate. The aggregate (across all sources) rate of data arriving.
- Process Rate. The aggregate (across all sources) rate at which Spark is processing data.
- Input Rows. The aggregate (across all sources) number of records processed in a trigger.
- Batch Duration. The process duration of each batch.
- Operation Duration. The amount of time taken to perform various operations in milliseconds.
The tracked operations are listed as follows.
- addBatch: Time taken to read the micro-batch’s input data from the sources, process it, and write the batch’s output to the sink. This should take the bulk of the micro-batch’s time.
- getBatch: Time taken to prepare the logical query to read the input of the current micro-batch from the sources.
- latestOffset & getOffset: Time taken to query the maximum available offset for this source.
- queryPlanning: Time taken to generates the execution plan.
- walCommit: Time taken to write the offsets to the metadata log.
- Global Watermark Gap. The gap between batch timestamp and global watermark for the batch.
- Aggregated Number Of Total State Rows. The aggregated number of total state rows.
- Aggregated Number Of Updated State Rows. The aggregated number of updated state rows.
- Aggregated State Memory Used In Bytes. The aggregated state memory used in bytes.
- Aggregated Number Of State Rows Dropped By Watermark. The aggregated number of state rows dropped by watermark.
As an early-release version, the statistics page is still under development and will be improved in future releases.
Streaming (DStreams) Tab
The web UI includes a Streaming tab if the application uses Spark Streaming with DStream API. This tab displays scheduling delay and processing time for each micro-batch in the data stream, which can be useful for troubleshooting the streaming application.
JDBC/ODBC Server Tab
We can see this tab when Spark is running as a distributed SQL engine. It shows information about sessions and submitted SQL operations.
The first section of the page displays general information about the JDBC/ODBC server: start time and uptime.
The second section contains information about active and finished sessions.
- User and IP of the connection.
- Session id link to access to session info.
- Start time, finish time and duration of the session.
- Total execute is the number of operations submitted in this session.
The third section has the SQL statistics of the submitted operations.
- User that submit the operation.
- Job id link to jobs tab.
- Group id of the query that group all jobs together. An application can cancel all running jobs using this group id.
- Start time of the operation.
- Finish time of the execution, before fetching the results.
- Close time of the operation after fetching the results.
- Execution time is the difference between finish time and start time.
- Duration time is the difference between close time and start time.
- Statement is the operation being executed.
- State of the process.
- Started, first state, when the process begins.
- Compiled, execution plan generated.
- Failed, final state when the execution failed or finished with error.
- Canceled, final state when the execution is canceled.
- Finished processing and waiting to fetch results.
- Closed, final state when client closed the statement.
- Detail of the execution plan with parsed logical plan, analyzed logical plan, optimized logical plan and physical plan or errors in the SQL statement.


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Gecode Reference Documentation
6.1.1
This document provides reference information about Gecode. The documentation is structured into three major groups: getting started, common programming tasks, and available functionality.
This document corresponds to Gecode version 6.1.1, please consult the changelog for recent changes.
Getting started
For your fist steps with Gecode, including detailed instructions on installing the library and compiling against it, please refer to the document Modeling and Programming with Gecode.
You may also want to have a look at our Notational conventions as well as our Example scripts (models).
Programming tasks
Documentation is available for the following tasks:
- Programming models
- Programming search engines
- Programming propagators and branchers
- Programming variables
- Testing
Available functionality
The most important functionality is:
The complete functionality can be found here.
The part Other available functionality documents existing propagators, variable implementations, and so on which serves as documentation of examples.
List and index content
Additionally, the documentation also features the following parts:
The following lists and indices are available


This story contains pages of image quizzes and image polls with the text direction set to right-to-left
4 option quiz
3 option quiz
2 option quiz
4 option poll
3 option poll
2 option poll


Control theory
Posted: 2016-12-06 , Modified: 2016-12-06
Tags: control theory
Posted: 2016-12-06 , Modified: 2016-12-06
Tags: control theory
where \(\al: [0,\iy)\to A\) is the control, \(r:\R^n\times A\to \R\) is the reward and \(g:\R^n\to \R\) is the terminal reward. The goal is to find the optimal \(\al\). (We can think of \(x\) as a function of \(t, \al, x^0\), \(x(t, \al, x^0)\).)
Example: Economics (investment) - \(x\) is output and \(\al\) is proportion to reinvest. \[\begin{align} \dot x &= k\al x\\ x(0)&=x^0\\ P(\al)&=\int_0^T (1-\al(t))x(t)\,dt. \end{align}\] Example: Try to stop a train with rockets on both sides - Here \(T\) is not fixed, but the \(\tau\), the first time that \((x,\dot x)=0\). \(\al\in [-1,1]\), \(x=\coltwo qv\). \[\begin{align} \dot x & = \matt 0100 x + \coltwo 01 \al\\ P(\al) & = -\tau \end{align}\]Let \(C(t)=\set{x}{\exists \al, x(t, \al, x^0)= x}\) and \(C=\bigcup_{t\ge 0} C(t)\).
Consider linear systems with solution \[\begin{align} \dot x &= Mx + \ub{N\al}{f}\\ X&=e^{tM}\\ x(t) &= X(t) x^0 + X(t) \int_0^t X^{-1}(s) f(s)\,ds. \end{align}\](If \(A=\R^n\), then \(\rank G=n \iff C=\R^n\).)
Suppose we observe \(y=Nx\) where \(N\in \R^{m\times n}\). Think of \(m<n\).
Say the system is observable if \(Nx_1\equiv Nx_2\) on \([0,t]\) implies \(x_1\equiv x_2\).
Duality. \(\dot x = Mx\), \(y=Nx\) is observable iff \(\dot z = M^Tz + N^T \al\), \(\al\in \R^m\) is controllable.
Proof.
Theorem. Any extreme point of the set of admissible controls \(\set{\al:\R^n\to [-1,1]^n}{x(t,\al,x^0)=x}\) has, for each \(t\ge 0\), \(i\), \(|\al^i|=1\) (is “bang-bang”). In particular, there always exists a bang-bang solution.
Proof.
For the linear system and \(A=[-1,1]^n\), there exist a time-optimal bang-bang solution. I.e. \(\tau^*=\inf \set{t}{x^0\in C(t)}\) is attainable.
Proof. Take \(t_n\to t\), \(\al_n\). Use Alaoglu.
Let the reachable set be \(K(t,x^0) = \set{x^1}{\exists \al, x(x^0, \al, t) = x^1}\). It is convex and closed (Pf. Alaoglu).
Theorem. There is \(h\) (depending on \(x_0\), but not on \(t\)) such that the optimal action is \[ \al^*(t) = \max_{a\in A} [h^T X^{-1}(t)Na]. \]
Proof.
(Take \(p(0) = h\), \(p=h^TX^{-1}\).)
Let \(L:\R^n\times \R^r\to \R\) (a Lagrangian). Suppose we want to solve (action equation) \[ \min I[x], \quad I[x] = \int_0^T L(x,\dot x)\,dt. \] Assume that \(p=\nb_v L(x,v)\) can be solved for \(v\). (How important is this?) The solution satisfies the Euler-Lagrange equation \[ \ddd t \ub{[\nb_v L(x^*, \dot x^*)]}{p} = \nb_x L(x^*, \dot x^*). \]
Proof. Consider “differentiating” in directoin \(y:[0,T]\to \R^n\), \(y(0)=y(T) = 0\). Consider \(i(\tau) = I[x+\tau y]\). \(i(\tau)\ge i(0)\) so \(i'(0)=0\). \[ i'(0) = \sumo in \int_0^T L_x(x,\dot x)y_i + L_{v_i} (x,\dot x) \dot y_i\,dt. \] Choose \(y = \psi(t) e_j\). IbP gives \(L_{x_j} - (L_{v_j})_t=0\).
The solution to EL satisfies Hamiltonian system: let \(H=p^Tv - L(x, v(x,p))\), \[\begin{align} \dot x &= \nb_p H\\ \dot p &= -\nb_x H. \end{align}\] Proof. \[\begin{align} \nb_x H &= p\nb_x v - \nb_x L - \nb_v L \nb_x v = -\nb_xL\\ \nb_p H &= v(p) + p^T \fc{Dv}{Dp} - \nb_p L \\ &= \dot x + p^T \fc{Dv}{Dp} - (\nb_v L)^T\fc{Dp}{Dv}=\dot x. \end{align}\](This is pretty confusing. \(v\) is implicitly defined in terms of \(p\), the value such that \(p=\nb_v L(x,v)\).)
Example: \[\begin{align} L &= \fc{m|v|^2}{2} - V(x)\\ m\ddot x &= -\nb V(x(t))\\ p &= \nb_v L = mv\\ H(x,p) &= \fc{|p|^2}{2m} + V. \end{align}\]4.2. Constraints create Lagrange multipliers, which contain valuable information. If \(x^*\in \pl R\), \(R=\{g\le 0\}\), \(x^*=\amax f\), then \(\nb f = \nb g\), \(\mu \nb f(x^*) = \la \nb g(x^*)\).
is \[ H(x,p,a) = f(x,a)^Tp+r(x,a)\]
(See warning on p. 50.)
Methodology: solve for \(\al(x,p)\), substitute back, solve the DE, then sub \(x,p\) into expression \(\al\). “Feedback controls”: set \(\al(t) = c(t)x(t)\) and write equation for \(c(t)\). (Cf. eigenfunctions??)
Transversality: adding condition to start in \(X_0\) and end in \(X_1\), we have \(p^*(\tau^*)\perp T_1\), \(p^*(0)\perp T_0\).
Adding a variable can help. Ex. \[ I(\al) = \iiy \redd{e^{-\al x}} \fc{\sin x}{x} \dx,\quad I'(\al) = -\rc{\al^2+1}. \]
Fix \(T\). Vary starting time and point: \[ v(x,t) = \sup_{\al \in A} P_{x,t}[\al]. \]
Hamilton-Jacobi-Bellman equation \[\begin{align} v_t + \ub{\max_{a\in A}[f\cdot \nb_x v + r]}{a^*(x,\nb_x v)} &= 0\\ v(x,T) & = g(x). \end{align}\] Proof. Taking the first equation, dividing by \(h\to 0\), using the chain rule \[\begin{align} v_t & \ge \int_t^{t+h} r\,ds + v(x(t+h), t+h) \\ v_t + \nb_x v \cdot x + r&\le 0. \end{align}\]Now take the max. Equality attained at optimal \(\al^*\).
General procedure;:
where \(K\) satisfies the matrix Riccati equation.
5.3. HJ equations…