Waching daily Aug 31 2017

When we first arrived to this place it was nearly empty

There was no one to talk to, nothing to do, not a single friend

But in spite of the loneliness you decided to stay

With pen and paper you started to make plans

"I want to show this hidden place to everyone else"

"I know they'll like it here, so that's why I'm asking for your help"

And so we put our hands to work, we started building a castle

A home where we'd never feel cold again

Lyrics, drawings and your emotions, little by little they start turning into songs

In order to make the foundation

Notes, chords, a melody; let my voice complete the harmony

Open the doors now

The dream we made come true together

Is an inspiration to many

And I'm so proud today, you know?

It makes me so happy to be able to say "I grew up by your side"

Shortly after more people came to live in the castle

It became so popular it filled up to the corridors

In order to make more room, other people also started building

"Everyone's going to help" was what they decided

Lots of talents and lots of love were poured into this task

There were some others who pushed it forward, turning it into a huge force

That's how that castle became surrounded by many other palaces

A community where there will always be room for everyone

Costumes, colors and photographs, together with choreographies

Passion became culture

A chorus of singing voices that joins us, even instruments I never imagined

Let this spread more and more

We built cities together

Where we made a connection

And I'm so proud today, you know?

It makes me so happy to be able to say...

That the world we created together

Is the greatest proof of love

And I'm so proud today, you know?

It makes me so happy to be able to say "I'm here with you"

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John DeGoes On Why You Should De-Risk Your BI Decision By Going With A Compiler - Duration: 5:20.

That's a good question

and I think

one of the

principles from functional programming,

actually is defer all the things

to the last possible moment

and it works out very well in practice,

because, like if you are throwing away information

and you're doing random things,

the deepest levels of your code,

it make things harder to understand

and harder to change later

and if you pull those decisions out,

if you pull the effects out

and push them to the outer edges of the program

it gives you a lot more flexibility

and it makes the code easier to reason about and so forth

and there's a similar principle in architectural design.

I think Slamdata is

the essence of that

attitude of deferring things to the last responsible moment

and what I mean by that is,

if you choose to be Isolution that's based on Spark

there's a lot of risk associated with that decision

and the reason is Spark is just

one analytics framework

to come along in the past 10 years

out of probably 50

and yet I know it's reasonably successful

but if you choose BI platform based on Spark,

you as a CIO are making a bet

that Spark's gonna be around 10 years from now

and it still gonna be supported and maintained

and it's gonna be the latest and greatest

and in my opinion,

history shows that

that is

very, very risky.

Before Spark there was MapReduce

and everyone thought MapReduce would be the end-all,

be-all of

computational

number crunching power

on Hadoop platforms

and of course that worked out spectacularly poorly.

Everyone who bet on MapReduce now has Legacy code bases

that

take hours or days to run,

that aren't well supported

by any of the major players in Hadoop

and that are written in these totally awkward,

cumbersome fashions

that are extremely difficult to maintain.

If you were a CIO, who bet on MapReduce,

as being the future of your

computational power of...

tower of number crunching capability,

then you bet wrong

and now you're gonna spend the next 10 years

paying down that technical debt

and it's the same way with Spark.

Spark is

a computational ejip

and BI tools that are powered by Spark

they work well, I mean reasonably well now,

but in my opinion,

history has shown us that

there will be something else after Spark,

whether that's Flink,

or whether it's Pachyderm

or whether it's

DataFlow or any one of the other numerous...

I mean literally dozens and dozens

of competing technologies out there

that are saying,

Spark got this wrong,

Spark got that wrong,

Spark got this wrong.

Let's do it this way, not that way

and Spark is unlikely to be able to be

the last computational framework

that is ever invented and adopted by industry.

It's likely to be just a next one

in a long line of successors

and so BI technology that's wedded to Spark

is hugely risky in my perspective

because it will be obsoleted

and the question is not if, it's when

and we've taken totally different approach,

which is we're not going to tire technology

to a specific number cruncher.

So we can take,

using our

core technology,

you take an L-Nix work flow

and we can compile it down to MapReduce,

that's just a connector, like Big Connector.

We can compile it down to Spark.

We can compile it down to whatever comes after Spark

and all of that technology is open source.

It's the Quasar Analytics super compiler project.

It's a 100% open source.

It's gonna be around forever

and what it allows you to do

is state what you want to do

but not how you want to do it

because what you want to do is probably not going to change.

You know you want to do the same sorts of analytics

now that you want to do in five years

and 10 years and so forth

but how do that is gonna depend on,

which of these projects ends up supplanting Spark

and in all likelihood, it's not going to be one,

there'll be lots of different technologies

for lots of different use cases

and Slamdata's approach

allows us to effectively support all of them

instead of wedding it,

like you know what Zoomdata has done with Spark,

wedding their technology to a single computational engine,

we said no, we're gonna defer that

and we're gonna support

all the different ways of approaching data.

We don't care, just bring in new data sources,

bring in new number crunchers or analytics engines

or databases or APIs and we don't care.

We're just gonna build the best compiler out there

and we're gonna make sure

that when some new source comes along,

we can support it in ideally a matter of days or weeks

by just smashing that cost down

and by putting all the smarts in our compiler technology.