Re: [DISCUSS] Flink SQL DDL Design

Wed, 05 Dec 2018 06:40:19 -0800 

Hi Jark and Shuyi,
thanks for pushing the DDL efforts forward. I agree that we should aim to combine both Shuyi's design and your design. 

Here are a couple of concerns that I think we should address in the design:


1. Scope: Let's focuses on a MVP DDL for CREATE TABLE statements first. 
I think this topic has already enough potential for long discussions and 
is very helpful for users. We can discuss CREATE VIEW and CREATE 
FUNCTION afterwards as they are not related to each other.



2. Constraints: I think we should consider things like nullability, 
VARCHAR length, and decimal scale and precision in the future as they 
allow for nice optimizations. However, since both the translation and 
runtime operators do not support those features. I would not introduce a 
arbitrary default value but omit those parameters for now. This can be a 
follow-up issue once the basic DDL has been merged.



3. Sources/Sinks: We had a discussion about CREATE TABLE vs CREATE 
[SOURCE|SINK|] TABLE before. In my opinion we should allow for these 
explicit declaration because in most production scenarios, teams have 
strict read/write access requirements. For example, a data science team 
should only consume from a event Kafka topic but should not accidently 
write back to the single source of truth.



4. Time attributes: In general, I like your computed columns approach 
because it makes defining a rowtime attributes transparent and simple. 
However, there are downsides that we should discuss.
4a. Jarks current design means that timestamps are in the schema twice. 
The design that is mentioned in [1] makes this more flexible as it 
either allows to replace an existing column or add a computed column.
4b. We need to consider the zoo of storage systems that is out there 
right now. Take Kafka as an example, how can we write out a timestamp 
into the message header? We need to think of a reverse operation to a 
computed column.
4c. Does defining a watermark really fit into the schema part of a 
table? Shouldn't we separate all time attribute concerns into a special 
clause next to the regular schema, similar how PARTITIONED BY does it in 
Hive?
4d. How can people come up with a custom watermark strategy? I guess 
this can not be implemented in a scalar function and would require some 
new type of UDF?



6. Partitioning and keys: Another question that the DDL design should 
answer is how do we express primary keys (for upserts), partitioning 
keys (for Hive, Kafka message keys). All part of the table schema?



5. Schema declaration: I find it very annoying that we want to force 
people to declare all columns and types again even though this is 
usually already defined in some company-wide format. I know that catalog 
support will greatly improve this. But if no catalog is used, people 
need to manually define a schema with 50+ fields in a Flink DDL. What I 
actually promoted having two ways of reading data:


1. Either the format derives its schema from the table schema.
CREATE TABLE (col INT) WITH (format.type = avro)


2. Or the table schema can be omitted and the format schema defines the 
table schema (+ time attributes).
CREATE TABLE WITH (format.type = avro, format.schema-file = 
"/my/avrofile.avsc")



Please let me know what you think about each item. I will try to 
incorporate your feedback in [1] this week.


Regards,
Timo


[1] 
https://docs.google.com/document/d/1Yaxp1UJUFW-peGLt8EIidwKIZEWrrA-pznWLuvaH39Y/edit#heading=h.41fd6rs7b3cf



Am 05.12.18 um 13:01 schrieb Jark Wu:

Hi Shuyi,

It's exciting to see we can make such a great progress here.

Regarding to the watermark:

Watermarks can be defined on any columns (including computed-column) in
table schema.
The computed column can be computed from existing columns using builtin
functions and *UserDefinedFunctions* (ScalarFunction).
So IMO, it can work out for almost all the scenarios not only common
scenarios.

I don't think using a `TimestampExtractor` to support custom timestamp
extractor in SQL is a good idea. Because `TimestampExtractor`
is not a SQL standard function. If we support `TimestampExtractor` in SQL,
do we need to support CREATE FUNCTION for `TimestampExtractor`?
I think `ScalarFunction` can do the same thing with `TimestampExtractor`
but more powerful and standard.

The core idea of the watermark definition syntax is that the schema part
defines all the columns of the table, it is exactly what the query sees.
The watermark part is something like a primary key definition or constraint
on SQL Table, it has no side effect on the schema, only defines what
watermark strategy is and makes which field as the rowtime attribute field.
If the rowtime field is not in the existing fields, we can use computed
column
to generate it from other existing fields. The Descriptor Pattern API [1]
is very useful when writing a Table API job, but is not contradictory to
the
Watermark DDL from my perspective.

[1]:
https://ci.apache.org/projects/flink/flink-docs-stable/dev/table/connect.html#rowtime-attributes
.

Best,
Jark

On Wed, 5 Dec 2018 at 17:58, Shuyi Chen <suez1...@gmail.com> wrote:


Hi Jark and Shaoxuan,

Thanks a lot for the summary. I think we are making great progress here.
Below are my thoughts.

*(1) watermark definition
IMO, it's better to keep it consistent with the rowtime extractors and
watermark strategies defined in

https://ci.apache.org/projects/flink/flink-docs-stable/dev/table/connect.html#rowtime-attributes
.
Using built-in functions seems to be too much for most of the common
scenarios.
*(2) CREATE SOURCE/SINK TABLE or CREATE TABLE
Actually, I think we can put the source/sink type info into the table
properties, so we can use CREATE TABLE.
(3) View DDL with properties
We can remove the view properties section now for the MVP and add it back
later if needed.
(4) Type Definition
I agree we can put the type length or precision into future versions. As
for the grammar difference, currently, I am using the grammar in Calcite
type DDL, but since we'll extend the parser in Flink, so we can definitely
change if needed.

Shuyi

On Tue, Dec 4, 2018 at 10:48 PM Jark Wu <imj...@gmail.com> wrote:


Hi Shaoxuan,

Thanks for pointing that out. Yes, the source/sink tag on create table is
the another major difference.

Summarize the main differences again:

*(1) watermark definition
*(2) CREATE SOURCE/SINK TABLE or CREATE TABLE
(3) View DDL with properties
(4) Type Definition

Best,
Jark

On Wed, 5 Dec 2018 at 14:08, Shaoxuan Wang <wshaox...@gmail.com> wrote:


Hi Jark,
Thanks for the summary. Your plan for the 1st round implementation of

DDL

looks good to me.
Have we reached the agreement on simplifying/unifying "create

[source/sink]

table" to "create table"? "Watermark definition" and "create table" are

the

major obstacles on the way to merge two design proposals FMPOV. @Shuyi,

It

would be great if you can spend time and respond to these two parts

first.

Regards,
Shaoxuan


On Wed, Dec 5, 2018 at 12:20 PM Jark Wu <imj...@gmail.com> wrote:


Hi Shuyi,

It seems that you have reviewed the DDL doc [1] that Lin and I

drafted.

This doc covers all the features running in Alibaba.
But some of features might be not needed in the first version of

Flink

SQL

DDL.

So my suggestion would be to focus on the MVP DDLs and reach

agreement

ASAP

based on the DDL draft [1] and the DDL design [2] Shuyi proposed.
And we can discuss on the main differences one by one.

The following is the MVP DDLs should be included in the first version

in

my

opinion (feedbacks are welcome):
(1) Table DDL:
     (1.1) Type definition
     (1.2) computed column definition
     (1.3) watermark definition
     (1.4) with properties
     (1.5) table constraint (primary key/unique)
     (1.6) column nullability (nice to have)
(2) View DDL
(3) Function DDL

The main differences from two DDL docs (sth maybe missed, welcome to

point

out):
*(1.3) watermark*: this is the main and the most important

difference,

it

would be great if @Timo Walther <twal...@apache.org>  @Fabian Hueske
<fhue...@gmail.com>  give some feedbacks.
  (1.1) Type definition:
       (a) Should VARCHAR carry a length, e.g. VARCHAR(128) ?
            In most cases, the varchar length is not used because they

are

stored as String in Flink. But it can be used to optimize in the

future

if

we know the column is a fixed length VARCHAR.
            So IMO, we can support VARCHAR with length in the future,

and

just VARCHAR in this version.
       (b) Should DECIMAL support custom scale and precision, e.g.
DECIMAL(12, 5)?
            If we clearly know the scale and precision of the Decimal,

we

can have some optimization on serialization/deserialization. IMO, we

can

support just support DECIMAL in this version,
            which means DECIMAL(38, 18) as default. And support custom

scale

and precision in the future.
  (2) View DDL: Do we need WITH properties in View DDL (proposed in

doc[2])?

What are the properties on the view used for?


The features could be supported and discussed in the future:
(1) period definition on table
(2) Type DDL
(3) Index DDL
(4) Library DDL
(5) Drop statement

[1] Flink DDL draft by Lin and Jark:



https://docs.google.com/document/d/1o16jC-AxnZoxMfHQptkKQkSC6ZDDBRhKg6gm8VGnY-k/edit#

[2] Flink SQL DDL design by Shuyi:



https://docs.google.com/document/d/1TTP-GCC8wSsibJaSUyFZ_5NBAHYEB1FVmPpP7RgDGBA/edit#

Cheers,
Jark

On Thu, 29 Nov 2018 at 16:13, Shaoxuan Wang <wshaox...@gmail.com>

wrote:

Sure Shuyu,
What I hope is that we can reach an agreement on DDL gramma as soon

as

possible. There are a few differences between your proposal and

ours.

Once

Lin and Jark propose our design, we can quickly discuss on the

those

differences, and see how far away towards a unified design.

WRT the external catalog, I think it is an orthogonal topic, we can

design

it in parallel. I believe @Xuefu, @Bowen are already working on. We
should/will definitely involve them to review the final design of

DDL

implementation. I would suggest that we should give it a higher

priority

on

the DDL implementation, as it is a crucial component for the user
experience of SQL_CLI.

Regards,
Shaoxuan



On Thu, Nov 29, 2018 at 6:56 AM Shuyi Chen <suez1...@gmail.com>

wrote:

Thanks a lot, Shaoxuan, Jack and Lin. We should definitely

collaborate

here, we have also our own DDL implementation running in

production

for

almost 2 years at Uber. With the joint experience from both

companies,

we

can definitely make the Flink SQL DDL better.

As @shaoxuan suggest, Jark can come up with a doc that talks

about

the

current DDL design in Alibaba, and we can discuss and merge them

into

one,

make it as a FLIP, and plan the tasks for implementation. Also,

we

should

take into account the new external catalog effort in the design.

What

do

you guys think?

Shuyi

On Wed, Nov 28, 2018 at 6:45 AM Jark Wu <imj...@gmail.com>

wrote:

Hi Shaoxuan,

I think summarizing it into a google doc is a good idea. We

will

prepare

it

in the next few days.

Thanks,
Jark

Shaoxuan Wang <wshaox...@gmail.com> 于2018年11月28日周三 下午9:17写道：


Hi Lin and Jark,
Thanks for sharing those details. Can you please consider

summarizing

your

DDL design into a google doc.
We can still continue the discussions on Shuyi's proposal.

But

having a

separate google doc will be easy for the DEV to

understand/comment/discuss

on your proposed DDL implementation.

Regards,
Shaoxuan


On Wed, Nov 28, 2018 at 7:39 PM Jark Wu <imj...@gmail.com>

wrote:

Hi Shuyi,

Thanks for bringing up this discussion and the awesome

work!

I

have

left

some comments in the doc.

I want to share something more about the watermark

definition

learned

from

Alibaba.

    1.

    Table should be able to accept multiple watermark

definition.

    Because a table may have more than one rowtime field.

For

example,

one

    rowtime field is from existing field but missing in some

records,

another
    is the ingestion timestamp in Kafka but not very

accurate.

In

this

case,

    user may define two rowtime fields with watermarks in

the

Table

and

choose
    one in different situation.
    2.

    Watermark stragety always work with rowtime field

together.

Based on the two points metioned above, I think we should

combine

the

watermark strategy and rowtime field selection (i.e. which

existing

field

used to generate watermark) in one clause, so that we can

define

multiple

watermarks in one Table.

Here I will share the watermark syntax used in Alibaba

(simply

modified):

watermarkDefinition:
WATERMARK [watermarkName] FOR <rowtime_field> AS

wm_strategy

wm_strategy:
   BOUNDED WITH OFFSET 'string' timeUnit
|
   ASCENDING

The “WATERMARK” keyword starts a watermark definition. The

“FOR”

keyword

defines which existing field used to generate watermark,

this

field

should

already exist in the schema (we can use computed-column to

derive

from

other fields). The “AS” keyword defines watermark strategy,

such

as

BOUNDED

WITH OFFSET (covers almost all the requirements) and

ASCENDING.

When the expected rowtime field does not exist in the

schema,

we

can

use

computed-column syntax to derive it from other existing

fields

using

built-in functions or user defined functions. So the

rowtime/watermark

definition doesn’t need to care about “field-change”

strategy

(replace/add/from-field). And the proctime field definition

can

also

be

defined using computed-column. Such as pt as PROCTIME()

which

defines a

proctime field named “pt” in the schema.

Looking forward to working with you guys!

Best,
Jark Wu


Lin Li <lincoln.8...@gmail.com> 于2018年11月28日周三 下午6:33写道：


@Shuyi
Thanks for the proposal!  We have a simple DDL

implementation

(extends

Calcite's parser) which been running for almost two years

on

production

and

works well.
I think the most valued things we'd learned is keeping

simplicity

and

standard compliance.
Here's the approximate grammar, FYI
CREATE TABLE

CREATE TABLE tableName(
         columnDefinition [, columnDefinition]*
         [ computedColumnDefinition [,

computedColumnDefinition]*

]

         [ tableConstraint [, tableConstraint]* ]
         [ tableIndex [, tableIndex]* ]
     [ PERIOD FOR SYSTEM_TIME ]
         [ WATERMARK watermarkName FOR rowTimeColumn AS
withOffset(rowTimeColumn, offset) ]     ) [ WITH (

tableOption

[

,

tableOption]* ) ] [ ; ]

columnDefinition ::=
         columnName dataType [ NOT NULL ]

dataType  ::=
         {
           [ VARCHAR ]
           | [ BOOLEAN ]
           | [ TINYINT ]
           | [ SMALLINT ]
           | [ INT ]
           | [ BIGINT ]
           | [ FLOAT ]
           | [ DECIMAL ]
           | [ DOUBLE ]
           | [ DATE ]
           | [ TIME ]
           | [ TIMESTAMP ]
           | [ VARBINARY ]
         }

computedColumnDefinition ::=
         columnName AS computedColumnExpression

tableConstraint ::=
     { PRIMARY KEY | UNIQUE }
         (columnName [, columnName]* )

tableIndex ::=
         [ UNIQUE ] INDEX indexName
          (columnName [, columnName]* )

rowTimeColumn ::=
         columnName

tableOption ::=
         property=value
         offset ::=
         positive integer (unit: ms)

CREATE VIEW

CREATE VIEW viewName
   [
         ( columnName [, columnName]* )
   ]
         AS queryStatement;

CREATE FUNCTION

  CREATE FUNCTION functionName
   AS 'className';

  className ::=
         fully qualified name


Shuyi Chen <suez1...@gmail.com> 于2018年11月28日周三 上午3:28写道：


Thanks a lot, Timo and Xuefu. Yes, I think we can

finalize

the

design

doc

first and start implementation w/o the unified

connector

API

ready

by

skipping some featue.

Xuefu, I like the idea of making Flink specific

properties

into

generic

key-value pairs, so that it will make integration with

Hive

DDL

(or

others,

e.g. Beam DDL) easier.

I'll run a final pass over the design doc and finalize

the

design

in

the

next few days. And we can start creating tasks and

collaborate

on

the

implementation. Thanks a lot for all the comments and

inputs.

Cheers!
Shuyi

On Tue, Nov 27, 2018 at 7:02 AM Zhang, Xuefu <

xuef...@alibaba-inc.com>

wrote:


Yeah! I agree with Timo that DDL can actually proceed

w/o

being

blocked

by

connector API. We can leave the unknown out while

defining

the

basic

syntax.

@Shuyi

As commented in the doc, I think we can probably

stick

with

simple

syntax

with general properties, without extending the syntax

too

much

that

it

mimics the descriptor API.

Part of our effort on Flink-Hive integration is also

to

make

DDL

syntax

compatible with Hive's. The one in the current

proposal

seems

making

our

effort more challenging.

We can help and collaborate. At this moment, I think

we

can

finalize

on

the proposal and then we can divide the tasks for

better

collaboration.

Please let me know if there are  any questions or

suggestions.

Thanks,
Xuefu






------------------------------------------------------------------

Sender:Timo Walther <twal...@apache.org>
Sent at:2018 Nov 27 (Tue) 16:21
Recipient:dev <dev@flink.apache.org>
Subject:Re: [DISCUSS] Flink SQL DDL Design

Thanks for offering your help here, Xuefu. It would

be

great

to

move

these efforts forward. I agree that the DDL is

somehow

releated

to

the

unified connector API design but we can also start

with

the

basic

functionality now and evolve the DDL during this

release

and

next

releases.

For example, we could identify the MVP DDL syntax

that

skips

defining

key constraints and maybe even time attributes. This

DDL

could

be

used

for batch usecases, ETL, and materializing SQL

queries

(no

time

operations like windows).

The unified connector API is high on our priority

list

for

the

1.8

release. I will try to update the document until mid

of

next

week.


Regards,

Timo


Am 27.11.18 um 08:08 schrieb Shuyi Chen:

Thanks a lot, Xuefu. I was busy for some other

stuff

for

the

last 2

weeks,

but we are definitely interested in moving this

forward.

I

think

once

the

unified connector API design [1] is done, we can

finalize

the

DDL

design

as

well and start creating concrete subtasks to

collaborate

on

the

implementation with the community.

Shuyi

[1]


https://docs.google.com/document/d/1Yaxp1UJUFW-peGLt8EIidwKIZEWrrA-pznWLuvaH39Y/edit?usp=sharing

On Mon, Nov 26, 2018 at 7:01 PM Zhang, Xuefu <

xuef...@alibaba-inc.com>

wrote:


Hi Shuyi,

I'm wondering if you folks still have the

bandwidth

working

on

this.

We have some dedicated resource and like to move

this

forward.

We

can

collaborate.

Thanks,

Xuefu




------------------------------------------------------------------

发件人：wenlong.lwl<wenlong88....@gmail.com>
日 期：2018年11月05日 11:15:35
收件人：<dev@flink.apache.org>
主 题：Re: [DISCUSS] Flink SQL DDL Design

Hi, Shuyi, thanks for the proposal.

I have two concerns about the table ddl:

1. how about remove the source/sink mark from the

ddl,

because

it

is

not

necessary, the framework determine the table

referred

is a

source

or a

sink

according to the context of the query using the

table.

it

will

be

more

convenient for use defining a table which can be

both

a

source

and

sink,

and more convenient for catalog to persistent and

manage

the

meta

infos.

2. how about just keeping one pure string map as

parameters

for

table,

like

create tabe Kafka10SourceTable (
intField INTEGER,
stringField VARCHAR(128),
longField BIGINT,
rowTimeField TIMESTAMP
) with (
connector.type = ’kafka’,
connector.property-version = ’1’,
connector.version = ’0.10’,
connector.properties.topic = ‘test-kafka-topic’,
connector.properties.startup-mode =

‘latest-offset’,

connector.properties.specific-offset = ‘offset’,
format.type = 'json'
format.prperties.version=’1’,
format.derive-schema = 'true'
);
Because:
1. in TableFactory, what user use is a string map

properties,

defining

parameters by string-map can be the closest way to

mapping

how

user

use

the

parameters.
2. The table descriptor can be extended by user,

like

what

is

done

in

Kafka

and Json, it means that the parameter keys in

connector

or

format

can

be

different in different implementation, we can not

restrict

the

key

in

a

specified set, so we need a map in connector scope

and a

map

in

connector.properties scope. why not just give

user a

single

map,

let

them

put parameters in a format they like, which is

also

the

simplest

way

to

implement DDL parser.
3. whether we can define a format clause or not,

depends

on

the

implementation of the connector, using different

clause

in

DDL

may

make

a

misunderstanding that we can combine the

connectors

with

arbitrary

formats,

which may not work actually.

On Sun, 4 Nov 2018 at 18:25, Dominik Wosiński <

wos...@gmail.com

wrote:

+1, Thanks for the proposal.

I guess this is a long-awaited change. This can

vastly

increase

the

functionalities of the SQL Client as it will be

possible

to

use

complex

extensions like for example those provided by

Apache

Bahir[1].

Best Regards,
Dom.

[1]
https://github.com/apache/bahir-flink

sob., 3 lis 2018 o 17:17 Rong Rong <

walter...@gmail.com>

napisał(a):

+1. Thanks for putting the proposal together

Shuyi.

DDL has been brought up in a couple of times

previously

[1,2].

Utilizing

DDL will definitely be a great extension to the

current

Flink

SQL

to

systematically support some of the previously

brought

up

features

such

as

[3]. And it will also be beneficial to see the

document

closely

aligned

with the previous discussion for unified SQL

connector

API

[4].

I also left a few comments on the doc. Looking

forward

to

the

alignment

with the other couple of efforts and

contributing

to

them!

Best,
Rong

[1]



http://mail-archives.apache.org/mod_mbox/flink-dev/201805.mbox/%3CCAMZk55ZTJA7MkCK1Qu4gLPu1P9neqCfHZtTcgLfrFjfO4Xv5YQ%40mail.gmail.com%3E

[2]



http://mail-archives.apache.org/mod_mbox/flink-dev/201810.mbox/%3CDC070534-0782-4AFD-8A85-8A82B384B8F7%40gmail.com%3E

[3]

https://issues.apache.org/jira/browse/FLINK-8003

[4]



http://mail-archives.apache.org/mod_mbox/flink-dev/201810.mbox/%3c6676cb66-6f31-23e1-eff5-2e9c19f88...@apache.org%3E

On Fri, Nov 2, 2018 at 10:22 AM Bowen Li <

bowenl...@gmail.com

wrote:

Thanks Shuyi!

I left some comments there. I think the design

of

SQL

DDL

and

Flink-Hive

integration/External catalog enhancements will

work

closely

with

each

other. Hope we are well aligned on the

directions

of

the

two

designs,

and I

look forward to working with you guys on both!

Bowen


On Thu, Nov 1, 2018 at 10:57 PM Shuyi Chen <

suez1...@gmail.com

wrote:

Hi everyone,

SQL DDL support has been a long-time ask from

the

community.

Current

Flink

SQL support only DML (e.g. SELECT and INSERT

statements).

In

its

current

form, Flink SQL users still need to

define/create

table

sources

and

sinks

programmatically in Java/Scala. Also, in SQL

Client,

without

DDL

support,

the current implementation does not allow

dynamical

creation

of

table,

type

or functions with SQL, this adds friction for

its

adoption.

I drafted a design doc [1] with a few other

community

members

that

proposes

the design and implementation for adding DDL

support

in

Flink.

The

initial

design considers DDL for table, view, type,

library

and

function.

It

will

be great to get feedback on the design from

the

community,

and

align

with

latest effort in unified SQL connector API [2]

and

Flink

Hive

integration

[3].

Any feedback is highly appreciated.

Thanks
Shuyi Chen

[1]



https://docs.google.com/document/d/1TTP-GCC8wSsibJaSUyFZ_5NBAHYEB1FVmPpP7RgDGBA/edit?usp=sharing

[2]



https://docs.google.com/document/d/1Yaxp1UJUFW-peGLt8EIidwKIZEWrrA-pznWLuvaH39Y/edit?usp=sharing

[3]



https://docs.google.com/document/d/1SkppRD_rE3uOKSN-LuZCqn4f7dz0zW5aa6T_hBZq5_o/edit?usp=sharing

--
"So you have to trust that the dots will

somehow

connect

in

your

future."



--
"So you have to trust that the dots will somehow

connect

in

your

future."


--
"So you have to trust that the dots will somehow connect in your

future."


--
"So you have to trust that the dots will somehow connect in your future."
































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