Feature: Vector-Column Transformations #291

ArvindSridhar · 2018-07-11T19:09:01Z

JIRA: MADLIB-1240

This commit adds a new SQL function called vec2cols and refactors the
current function cols2vec, providing greater integration between the two
modules. We now have a single Python file with separate classes for each
feature. We also have unified unit-tests and dev-check/install-check
tests.

The vec2cols function enables users to split up a single column into
multiple columns, given that the input column contains array entries.
For example, if the input column contained ARRAY[1, 2, 3] in one of its
rows, the output table will contain 3 different columns, one for each
element of the array.

asfgit · 2018-07-11T19:32:35Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/545/

iyerr3

Functionality on its own LGTM. There might be overlap of code between this and #288. It would help to have a unified code structure for the two functions.

iyerr3 · 2018-07-12T00:14:47Z

src/ports/postgres/modules/internal/test/unit_tests/test_db_utils.py_in

+import plpy_mock as plpy
+
+m4_changequote(`<!', `!>')
+class Vec2ColsTestCase(unittest.TestCase):


There is another Vec2ColsTestCase in test_vec2cols.py_in. Is this one redundant?

Great catch haha, this was a typo. Updating the other PR now.

iyerr3 · 2018-07-12T00:15:09Z

src/ports/postgres/modules/utilities/test/unit_tests/test_utilities.py_in

@@ -243,6 +243,9 @@ class UtilitiesTestCase(unittest.TestCase):
        self.assertFalse(s.is_valid_psql_type('boolean[]', s.INCLUDE_ARRAY | s.ONLY_ARRAY))
        self.assertFalse(s.is_valid_psql_type('boolean', s.ONLY_ARRAY))
        self.assertFalse(s.is_valid_psql_type('boolean[]', s.ONLY_ARRAY))
+        self.assertTrue(s.is_valid_psql_type('boolean[]', s.ANY_ARRAY))


Can we move this and corresponding code changes to another commit and PR?

Done, should be on PRs 292 and 293

iyerr3 · 2018-07-12T00:23:54Z

src/ports/postgres/modules/utilities/vec2cols.py_in

+        @param: feature_names, list. Python list of the feature names to
+                use for the split elements in the vector_col array
+    """
+    query = """


I'm assuming this was meant to use the is_col_1d_array function?

fmcquillan99 · 2018-07-12T17:37:14Z

user docs seem incomplete

asfgit · 2018-07-12T18:37:52Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/551/

asfgit · 2018-07-13T00:51:13Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/556/

asfgit · 2018-07-14T01:10:59Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/560/

asfgit · 2018-07-17T03:29:21Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/566/

asfgit · 2018-07-17T03:43:47Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/567/

asfgit · 2018-07-17T22:36:08Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/568/

asfgit · 2018-07-18T05:50:25Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/569/

asfgit · 2018-07-18T12:30:44Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/570/

asfgit · 2018-07-18T19:18:39Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/571/

iyerr3 · 2018-07-18T20:34:30Z

Please note that cols2vec.py_in failed rat check due to missing license header.

ArvindSridhar · 2018-07-18T23:21:40Z

PR is ready to be reviewed once again

asfgit · 2018-07-19T02:55:31Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/574/

fmcquillan99 · 2018-07-19T18:33:43Z

In cols2vec,

For this table:

CREATE TABLE golf (
    id integer NOT NULL,
    "OUTLOOK" text,
    temperature double precision,
    humidity double precision,
    "Temp_Humidity" double precision[],
    clouds_airquality text[],
    windy boolean,
    class text,
    observation_weight double precision
);

this fails:

SELECT madlib.cols2vec(
    'golf',
    'cols2vec_result',
    'id, temperature'
);

because id is INT and temperature is FLOAT.

It forces the user to do:

SELECT madlib.cols2vec(
    'golf',
    'cols2vec_result',
    'id::FLOAT, temperature'
);

but this is inconvenient especially if you have a big
table and are using '*' to get all columns into the feature
vector and they are a mix of numeric types.

Also a mix of VARCHAR and TEXT fails in a similar way
but should not.

Use PostgreSQL precendence rules to fix this please.

fmcquillan99 · 2018-07-19T20:14:15Z

In vec2cols,

SELECT madlib.vec2cols(
    'golf',                           -- source table
    'vec2cols_result',                -- output table
    'clouds_airquality',              -- column with array entries to split
    ARRAY['clouds', 'air_quality'],   -- feature names
    '"OUTLOOK", id'                   -- columns to keep from source table
);

results in

 clouds | air_quality | OUTLOOK  | id
--------+-------------+----------+----
 none   | unhealthy   | sunny    |  1
 none   | moderate    | sunny    |  2
 low    | moderate    | overcast |  3
 low    | moderate    | rain     |  4
 medium | good        | rain     |  5
 low    | unhealthy   | rain     |  6
 medium | moderate    | overcast |  7
 high   | unhealthy   | sunny    |  8
 high   | good        | sunny    |  9
 medium | good        | rain     | 10
 none   | good        | sunny    | 11
 medium | moderate    | overcast | 12
 medium | moderate    | overcast | 13
 low    | unhealthy   | rain     | 14
(14 rows)

but the split columns clouds and air_quality should
be the right side of the table. This will make
it consistent with the way cols2vec works where the
the new stuff is put on the right side of the table.

fmcquillan99 · 2018-07-19T20:18:01Z

After the above 2 issues I mentioned are fixed, I will have 1 more commit on user docs to this PR

asfgit · 2018-07-19T21:25:17Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/582/

njayaram2 · 2018-07-19T22:19:13Z

src/ports/postgres/modules/utilities/transform_vec_cols.py_in

+        """
+        input_tbl_valid(source_table, self.module_name)
+        output_tbl_valid(output_table, self.module_name)
+        # cols_to_validate = self.get_cols_helper.get_cols_as_list(cols_to_output) + [vector_col]


Guess we can remove this commented line.

njayaram2 · 2018-07-19T22:25:17Z

src/ports/postgres/modules/utilities/transform_vec_cols.py_in

+        cols_to_keep = ', '.join(self.get_cols_helper.get_cols_as_list(cols_to_output,
+                                 source_table)) + ", " if cols_to_output else ''
+
+        # TODO why don't we call quote_literal here but call it later for feature_cols


Could we have a comment explaining this?

njayaram2 · 2018-07-19T22:25:28Z

src/ports/postgres/modules/utilities/transform_vec_cols.py_in

+
+        output_table_summary = add_postfix(output_table, "_summary")
+        # Dollar-quote the text to allow single-quotes without escaping
+        # TODO explain why it's called _outer_


Is this still valid?

asfgit · 2018-07-20T01:43:04Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/583/

ArvindSridhar · 2018-07-20T17:48:39Z

All PR comments addressed, commits have been squashed and pushed to this branch, ready to finalize PR

asfgit · 2018-07-20T17:53:20Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/584/

asfgit · 2018-07-25T23:38:19Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/603/

asfgit · 2018-07-26T00:24:21Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/605/

asfgit · 2018-07-26T00:47:57Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/606/

asfgit · 2018-07-26T01:04:05Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/607/

asfgit · 2018-07-26T18:19:37Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/608/

asfgit · 2018-07-26T19:03:22Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/609/

iyerr3 · 2018-07-27T20:56:03Z

src/ports/postgres/modules/utilities/transform_vec_cols.py_in

+        distinct_types = set([col_type[1] for col_type in all_cols_and_types
+            if col_type[0] in self.features_to_nest])
+        for expr_type in distinct_types:
+            _assert(not is_valid_psql_type(expr_type, ANY_ARRAY),


This is more cleanly written as

_assert(not any(is_valid_psql_type(expr_type, ANY_ARRAY) for expr_type in distinc_types), ...

iyerr3 · 2018-07-27T20:57:40Z

src/ports/postgres/modules/utilities/validate_args.py_in

@@ -513,11 +513,12 @@ def array_col_has_same_dimension(tbl, col):
 # ------------------------------------------------------------------------


-def explicit_bool_to_text(tbl, cols, schema_madlib):
+def explicit_bool_to_text(tbl, cols, schema_madlib, is_forced=False):


I'm not clear on the need for is_forced. Are there platforms that have a bool-to-text cast require this patching?

w/ @ArvindSridhar On platforms that has bool to text casting (gpdb5, pg 9.6, pg 10), we still need this to make sure we can create an array of bool and text types.

We don't need this function, though - we might need ::TEXT. But I believe we decided that we'll let the platform fail if the array cannot be built by it. Wouldn't this build a successful array when the platform is failing?

That's a good point-we added this arg to make our dev-check pass, because our dev check didn't have an explicit ::TEXT cast and yet it was running on PG10, which supports bool to text casting. Would removing the dev check test and the is_forced arg be the better way to go?

iyerr3 · 2018-07-27T20:58:26Z

src/ports/postgres/modules/utilities/utilities.py_in

@@ -221,11 +221,11 @@ def is_psql_numeric_type(arg, exclude=None):
    Returns:
        Boolean. Returns if 'arg' is one of the numeric types
    """
-    numeric_types = set(['smallint', 'integer', 'bigint', 'decimal', 'numeric',
-                         'real', 'double precision', 'serial', 'bigserial'])
+    # numeric_types = set(['smallint', 'integer', 'bigint', 'decimal', 'numeric',


These lines (+ other similar lines below) can be deleted.

iyerr3 · 2018-07-27T20:59:04Z

src/ports/postgres/modules/utilities/transform_vec_cols.py_in

+            _assert(not is_valid_psql_type(expr_type, ANY_ARRAY),
+                "{0}: Feature columns to nest cannot be of type array"
+                .format(self.module_name))
+        if len(distinct_types) != 1 and 'boolean' in distinct_types:


Please help me understand the need for len(distinct_types) != 1

We want to cast boolean to text only if it is mixed with other types. Creating a vector of multiple boolean columns works without casting.

Makes sense. I would suggest changing it to len(distinct_types) > 1 and adding what you said above as a comment.

asfgit · 2018-07-27T23:04:26Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/614/

ArvindSridhar · 2018-07-30T17:45:13Z

Removed the problematic dev check test that required us to use forced bool to text conversion, should be good to go

asfgit · 2018-07-30T18:10:27Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/617/

JIRA: MADLIB-1240 This commit adds a new SQL function called vec2cols and refactors the current function cols2vec, providing greater integration between the two modules. We now have a single Python file with separate classes for each feature. We also have unified unit-tests and dev-check/install-check tests. The vec2cols function enables users to split up a single column into multiple columns, given that the input column contains array entries. For example, if the input column contained ARRAY[1, 2, 3] in one of its rows, the output table will contain 3 different columns, one for each element of the array. Co-authored-by: Nandish Jayaram <njayaram@apache.org> Co-authored-by: Rahul Iyer <riyer@apache.org> Co-authored-by: Nikhil Kak <nkak@pivotal.io>

Co-authored-by: Nikhil Kak <nkak@pivotal.io>

Removes type validation from the code and instead lets the underlying database handle type exceptions and casting. Updated dev-check and unit-tests accordingly. Co-authored-by: Orhan Kislal <okislal@pivotal.io>

asfgit · 2018-07-30T20:03:38Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/619/

fmcquillan99 · 2018-07-31T21:26:42Z

Where did we land on the boolean casting issue? Testing on Greenplum 5, I see:

(psycopg2.ProgrammingError) plpy.SPIError: ARRAY types boolean and text cannot be matched
CONTEXT:  Traceback (most recent call last):
  PL/Python function "cols2vec", line 23, in <module>
    return cols2vec_obj.cols2vec(**globals())
  PL/Python function "cols2vec", line 363, in cols2vec
PL/Python function "cols2vec"
 [SQL: "SELECT madlib.cols2vec(\n    'golf',\n    'cols2vec_result',\n    'windy, class'\n);"]

(psycopg2.ProgrammingError) plpy.SPIError: ARRAY types integer and boolean cannot be matched
CONTEXT:  Traceback (most recent call last):
  PL/Python function "cols2vec", line 23, in <module>
    return cols2vec_obj.cols2vec(**globals())
  PL/Python function "cols2vec", line 363, in cols2vec
PL/Python function "cols2vec"
 [SQL: "SELECT madlib.cols2vec(\n    'golf',\n    'cols2vec_result',\n    'temperature, windy'\n);"]

fmcquillan99 · 2018-07-31T21:37:24Z

Wondering about order for varchar and text casting.
For this data set:

DROP TABLE IF EXISTS golf CASCADE;

CREATE TABLE golf (
    id int,
    "OUTLOOK" varchar,
    temperature smallint,
    humidity real,
    "Temp_Humidity" double precision[],
    clouds_airquality text[],
    windy boolean,
    class text,
    observation_weight double precision
);

INSERT INTO golf VALUES
(1,'sunny', 85, 85, ARRAY[85, 85],ARRAY['none', 'unhealthy'], 'false','Don''t Play', 5.0),
(2, 'sunny', 80, 90, ARRAY[80, 90], ARRAY['none', 'moderate'], 'true', 'Don''t Play', 5.0),
(3, 'overcast', 83, 78, ARRAY[83, 78], ARRAY['low', 'moderate'], 'false', 'Play', 1.5),
(4, 'rain', 70, 96, ARRAY[70, 96], ARRAY['low', 'moderate'], 'false', 'Play', 1.0),
(5, 'rain', 68, 80, ARRAY[68, 80], ARRAY['medium', 'good'], 'false', 'Play', 1.0),
(6, 'rain', 65, 70, ARRAY[65, 70], ARRAY['low', 'unhealthy'], 'true', 'Don''t Play', 1.0),
(7, 'overcast', 64, 65, ARRAY[64, 65], ARRAY['medium', 'moderate'], 'true', 'Play', 1.5),
(8, 'sunny', 72, 95, ARRAY[72, 95], ARRAY['high', 'unhealthy'], 'false', 'Don''t Play', 5.0),
(9, 'sunny', 69, 70, ARRAY[69, 70], ARRAY['high', 'good'], 'false', 'Play', 5.0),
(10, 'rain', 75, 80, ARRAY[75, 80], ARRAY['medium', 'good'], 'false', 'Play', 1.0),
(11, 'sunny', 75, 70, ARRAY[75, 70], ARRAY['none', 'good'], 'true', 'Play', 5.0),
(12, 'overcast', 72, 90, ARRAY[72, 90], ARRAY['medium', 'moderate'], 'true', 'Play', 1.5),
(13, 'overcast', 81, 75, ARRAY[81, 75], ARRAY['medium', 'moderate'], 'false', 'Play', 1.5),
(14, 'rain', 71, 80, ARRAY[71, 80], ARRAY['low', 'unhealthy'], 'true', 'Don''t Play', 1.0);

(1)

DROP TABLE IF EXISTS cols2vec_result, cols2vec_result_summary;

SELECT madlib.cols2vec(
    'golf',
    'cols2vec_result',
    '"OUTLOOK", class'
);

produces a varchar array:

select *                                                                                                                                                  from INFORMATION_SCHEMA.COLUMNS where table_name = 'out99';
-[ RECORD 1 ]------------+------------------
table_catalog            | madlib
table_schema             | public
table_name               | out99
column_name              | f2
ordinal_position         | 2
column_default           | 
is_nullable              | YES
data_type                | character varying
character_maximum_length | 
character_octet_length   | 1073741824
numeric_precision        | 
numeric_precision_radix  | 
numeric_scale            | 
datetime_precision       | 
interval_type            | 
interval_precision       | 
character_set_catalog    | 
character_set_schema     | 
character_set_name       | 
collation_catalog        | 
collation_schema         | 
collation_name           | 
domain_catalog           | 
domain_schema            | 
domain_name              | 
udt_catalog              | madlib
udt_schema               | pg_catalog
udt_name                 | varchar
scope_catalog            | 
scope_schema             | 
scope_name               | 
maximum_cardinality      | 
dtd_identifier           | 2
is_self_referencing      | NO
is_identity              | NO
identity_generation      | 
identity_start           | 
identity_increment       | 
identity_maximum         | 
identity_minimum         | 
identity_cycle           | 
is_generated             | NEVER
generation_expression    | 
is_updatable             | YES
-[ RECORD 2 ]------------+------------------
table_catalog            | madlib
table_schema             | public
table_name               | out99
column_name              | f1
ordinal_position         | 1
column_default           | 
is_nullable              | YES
data_type                | character varying
character_maximum_length | 
character_octet_length   | 1073741824
numeric_precision        | 
numeric_precision_radix  | 
numeric_scale            | 
datetime_precision       | 
interval_type            | 
interval_precision       | 
character_set_catalog    | 
character_set_schema     | 
character_set_name       | 
collation_catalog        | 
collation_schema         | 
collation_name           | 
domain_catalog           | 
domain_schema            | 
domain_name              | 
udt_catalog              | madlib
udt_schema               | pg_catalog
udt_name                 | varchar
scope_catalog            | 
scope_schema             | 
scope_name               | 
maximum_cardinality      | 
dtd_identifier           | 1
is_self_referencing      | NO
is_identity              | NO
identity_generation      | 
identity_start           | 
identity_increment       | 
identity_maximum         | 
identity_minimum         | 
identity_cycle           | 
is_generated             | NEVER
generation_expression    | 
is_updatable             | YES

(2)

DROP TABLE IF EXISTS cols2vec_result, cols2vec_result_summary;

SELECT madlib.cols2vec(
    'golf',
    'cols2vec_result',
    'class, "OUTLOOK"'
);

produces a text array:

select *                                                                                                                                                  from INFORMATION_SCHEMA.COLUMNS where table_name = 'out99';
-[ RECORD 1 ]------------+-----------
table_catalog            | madlib
table_schema             | public
table_name               | out99
column_name              | f2
ordinal_position         | 2
column_default           | 
is_nullable              | YES
data_type                | text
character_maximum_length | 
character_octet_length   | 1073741824
numeric_precision        | 
numeric_precision_radix  | 
numeric_scale            | 
datetime_precision       | 
interval_type            | 
interval_precision       | 
character_set_catalog    | 
character_set_schema     | 
character_set_name       | 
collation_catalog        | 
collation_schema         | 
collation_name           | 
domain_catalog           | 
domain_schema            | 
domain_name              | 
udt_catalog              | madlib
udt_schema               | pg_catalog
udt_name                 | text
scope_catalog            | 
scope_schema             | 
scope_name               | 
maximum_cardinality      | 
dtd_identifier           | 2
is_self_referencing      | NO
is_identity              | NO
identity_generation      | 
identity_start           | 
identity_increment       | 
identity_maximum         | 
identity_minimum         | 
identity_cycle           | 
is_generated             | NEVER
generation_expression    | 
is_updatable             | YES
-[ RECORD 2 ]------------+-----------
table_catalog            | madlib
table_schema             | public
table_name               | out99
column_name              | f1
ordinal_position         | 1
column_default           | 
is_nullable              | YES
data_type                | text
character_maximum_length | 
character_octet_length   | 1073741824
numeric_precision        | 
numeric_precision_radix  | 
numeric_scale            | 
datetime_precision       | 
interval_type            | 
interval_precision       | 
character_set_catalog    | 
character_set_schema     | 
character_set_name       | 
collation_catalog        | 
collation_schema         | 
collation_name           | 
domain_catalog           | 
domain_schema            | 
domain_name              | 
udt_catalog              | madlib
udt_schema               | pg_catalog
udt_name                 | text
scope_catalog            | 
scope_schema             | 
scope_name               | 
maximum_cardinality      | 
dtd_identifier           | 1
is_self_referencing      | NO
is_identity              | NO
identity_generation      | 
identity_start           | 
identity_increment       | 
identity_maximum         | 
identity_minimum         | 
identity_cycle           | 
is_generated             | NEVER
generation_expression    | 
is_updatable             | YES

Why is that?

ArvindSridhar · 2018-07-31T22:53:23Z

Regarding bool to text/integer conversion in GPDB5, I believe you have to use an explicit cast as required by the underlying platform. Thus, if you "temperature, windy::integer" or "windy::text, class", it should work fine. This is how the underlying postgres syntax for GPDB5 works as well
For the text-varchar ordering, my hunch is that postgres treats these types as having the same priority, and thus just casts the second argument to whatever type the first argument was in.

fmcquillan99 · 2018-08-01T00:47:54Z

thanks, that makes sense.

I added a type casting example to the user docs.

LGTM

asfgit · 2018-08-01T01:13:36Z

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/628/

iyerr3 reviewed Jul 12, 2018

View reviewed changes

ArvindSridhar force-pushed the feature/vector-to-columns branch from 1e8bc32 to 3fb2c43 Compare July 12, 2018 18:11

iyerr3 mentioned this pull request Jul 12, 2018

Internal: Add function to check column type for 1D array #292

Closed

ArvindSridhar force-pushed the feature/vector-to-columns branch from 3fb2c43 to 543dad5 Compare July 13, 2018 00:27

ArvindSridhar force-pushed the feature/vector-to-columns branch from b580664 to 0d31b49 Compare July 17, 2018 00:34

ArvindSridhar force-pushed the feature/vector-to-columns branch from 7ed9ac8 to e0aa087 Compare July 18, 2018 00:15

ArvindSridhar force-pushed the feature/vector-to-columns branch from e0aa087 to ef23f3a Compare July 18, 2018 22:47

njayaram2 reviewed Jul 19, 2018

View reviewed changes

ArvindSridhar force-pushed the feature/vector-to-columns branch from 2013aad to a3c51a2 Compare July 20, 2018 17:46

ArvindSridhar force-pushed the feature/vector-to-columns branch from 9b443f3 to 4b77a37 Compare July 26, 2018 18:38

iyerr3 reviewed Jul 27, 2018

View reviewed changes

ArvindSridhar and others added 6 commits July 30, 2018 12:36

Internal: Add function to check column type for 1D array

7374286

Co-authored-by: Nikhil Kak <nkak@pivotal.io>

fix column order in examples in vec2cols user docs

5c566d7

Utilities: Vector-Column Type Casting Fixes

1a61967

Removes type validation from the code and instead lets the underlying database handle type exceptions and casting. Updated dev-check and unit-tests accordingly. Co-authored-by: Orhan Kislal <okislal@pivotal.io>

Code clean-up

097613b

Removed dev check test regarding forcing of explicit bool to text

1a7c756

ArvindSridhar force-pushed the feature/vector-to-columns branch from 3d72503 to 1a7c756 Compare July 30, 2018 19:37

minor cols2vec user doc updates

19ee891

asfgit closed this in 20f95b3 Aug 1, 2018

Feature: Vector-Column Transformations #291

Feature: Vector-Column Transformations #291

Conversation

ArvindSridhar commented Jul 11, 2018 • edited Loading

asfgit commented Jul 11, 2018

iyerr3 left a comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

fmcquillan99 commented Jul 12, 2018

asfgit commented Jul 12, 2018

asfgit commented Jul 13, 2018

asfgit commented Jul 14, 2018

asfgit commented Jul 17, 2018

asfgit commented Jul 17, 2018

asfgit commented Jul 17, 2018

asfgit commented Jul 18, 2018

asfgit commented Jul 18, 2018

asfgit commented Jul 18, 2018

iyerr3 commented Jul 18, 2018

ArvindSridhar commented Jul 18, 2018

asfgit commented Jul 19, 2018

fmcquillan99 commented Jul 19, 2018

fmcquillan99 commented Jul 19, 2018 • edited Loading

fmcquillan99 commented Jul 19, 2018

asfgit commented Jul 19, 2018

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

asfgit commented Jul 20, 2018

ArvindSridhar commented Jul 20, 2018

asfgit commented Jul 20, 2018

asfgit commented Jul 25, 2018

asfgit commented Jul 26, 2018

asfgit commented Jul 26, 2018

asfgit commented Jul 26, 2018

asfgit commented Jul 26, 2018

asfgit commented Jul 26, 2018

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

iyerr3 Jul 27, 2018 • edited Loading

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

asfgit commented Jul 27, 2018

ArvindSridhar commented Jul 30, 2018

asfgit commented Jul 30, 2018

asfgit commented Jul 30, 2018

fmcquillan99 commented Jul 31, 2018

fmcquillan99 commented Jul 31, 2018

ArvindSridhar commented Jul 31, 2018

fmcquillan99 commented Aug 1, 2018

asfgit commented Aug 1, 2018

ArvindSridhar commented Jul 11, 2018 •

edited

Loading

fmcquillan99 commented Jul 19, 2018 •

edited

Loading

iyerr3 Jul 27, 2018 •

edited

Loading