Common tools from Sales Engineering

This is a public repo to contain libraries, utilities, and other resources created by Sales Engineering and others to support and enhance ongoing and future RAI projects. These resources are not client-specific, can be freely shared, distributed and updated in the spirit of OSS.

Free License is pending.

Command-line tools and environment

Bash, Python, Julia, etc., tools for command line usage.

• envcli_template.sh
  Copy this template to create your own envcli.sh scripts, customized to each RAI project you work on.

  The bash scripts execute source envcli.sh to get your preferences for:

  • RAI_CLI_PROFILE - the ~/.rai/config profile with your OAuth credentials (which match a specific RAI account)
  • RAI_CLI_ENGINE - your default Rel engine name in that RAI account
  • RAI_CLI_DATABASE - your default database in that RAI account
  • RAI_BENCH_DIR - your directory with the Basic Workload Benchmarks framework code

• bin/...
  Bash scripts to simplify use of the CLI for RAI account management tasks.

  • clone_database.sh - create clone of an existing database in account RAI_CLI_PROFILE. Syntax follows Linux command conventions (cp, mv, etc): clone_database.sh source-db clone-db.
  • create_engine.sh - spin up new Rel engine. The default name is specified by RAI_CLI_ENGINE variable, but a different name can be specified on the command line.
  • create_project_skel.sh - create the directory structure for a new customer project
  • delete_engine.sh - spin down an existing Rel engine. The default name is specified by RAI_CLI_ENGINE variable, but a different name can be specified on the command line.
  • list_databases.sh - list the databases in account RAI_CLI_PROFILE.
  • list_edb_names.sh - list the EDBs in database RAI_CLI_DATABASE, in account RAI_CLI_PROFILE.
  • list_engines.sh - list the active engines in account RAI_CLI_PROFILE.
  • load_source.sh - load specified Rel source file into RAI_CLI_DATABASE, using RAI_CLI_ENGINE, in account RAI_CLI_PROFILE. The relative path to the Rel source is preserved in the RAI model unless old/new reparenting directories are specified.
  • rai_bench_results_summary.sh - generate human-readable summary results from the JSON Lines (*.jsonl) files in a Basic Workloads Benchmark framework ("RAI bench") output directory. The location of the Basic Workloads directory is specified in RAI_BENCH_DIR. The most recent output directory is used by default, but a different name can be specified on the command line.

  Python tools for testing.

  • parse_csv.py - use Python's csv reader to explore customer-provided CSV files (if RAI's load_csv doesn't behave as expected). Use parse_csv.py --file foo.csv --top 5 --full to get started. Use parse_csv.py --help for full help.

SE Rel library

Folder se_lib contains Rel models for with various sets of utilities:

• csv.rel: CSV file parsing and loading

• query.rel: Tools for querying and poking around RAI database relations

• kg.rel: functions to construct, manipulate, operate on and visualize knowledge graphs based on standard data model

• graph.rel: functions to operate on Rel graph objects

• util.rel: collection of useful general purpose functions supplementing standard library functions

• viz.rel: helper functions for graphviz, vega/vega-lite, and other visualization libraries

• visual.rel (DEPRECATED: do not use or stop using): graphviz-based visualization functions for knowledge graphs, ontology, etc.

• debug.rel: TBD

util.rel

kg.rel

Options (Configuration) Module Format

Example of options module (OPTS) passed to knowledge graph functions:

module kg_options
  module graphviz
    def title = "Knowledge Graph" // Graph Title
    def layout = "dot"
    def direction = "TD"
    def entity_shape = {(:Customer, "oval");
                        (:Bank, "box");}
    def label_edges = boolean_false
  end
end

Knowldge graph visualization functions take ...

csv.rel

To parse and map a CSV file into standard model use utility function parse_attributes defined in csv.rel.

Below is example from IMDB demo (see imdb_model notebook for full code).

Importing CSV file into RAI

Suppose we have CSV file containing IMDB titles that has been loaded from Azure store like this:

// Title CSV
@no_diagnostics(:UNDEFINED_IDENTIFIER)
def delete[:title_csv] = title_csv
def title_config:path = "s3://psilabs-public-files/imdb/title_basics_1953_votes_30.csv"
def insert[:title_csv] = lined_csv[load_csv[title_config]]

Defining Entity Type

The data will be used to create and populate entity Title. For this purpose we define several auxilary modules. First, module create_entity defines entity Title and its constructor function title_from_id:

entity type Title = String
entity type Name = String

module create_entity
    def Title[x] = ^Title[x]
    def title_from_id(id, e) = create_entity:Title[id](e) and
                                title_csv(imdb_meta:title:key, _, id)

    def Name[x] = ^Name[x]
    def name_from_id(id, e) = create_entity:Name[id](e) and
                                name_csv(imdb_meta:name:key, _, id)
end

Declaring Metadata

Note, that we already used element from another auxilary module imdb_meta that defines all necessary metadata to load, parse, and define Title entity from CSV:

module imdb_meta

    module title
        def entity_name = :Title
        def key = :tconst
        def as_is_attr = {
            :primaryTitle;
            :titleType;
        }
        def int_attr = {
            :startYear; :endYear; :numVotes; :runtimeMinutes;
        }
        def float_attr = {
            :averageRating
        }
        def attr_alias_map = {
            (:tconst, :id);
        }
    end

    module name
        def entity_name = :Name
        def key = :nconst
        def as_is_attr = {
            :primaryName;
            :primaryProfession;
        }
        def int_attr = {
            :birthYear; :deathYear;
        }
        def attr_alias_map = {
            (:nconst, :id);
        }
    end

end

There are more elements meta module may define depending on CSV file content, for example, it could also define datetime_attr and date_attr.

Let's review what meta module does.

First, we always define entity_name (usually by capitalizing first letter) and key (only single value keys are supported currently) like this:

def enity_name = :Title
def key = :tconst

Next, we define fields according to their types. If the field type doesn't change from the one parsed/recognized by load_csv then it belongs to as_is_attr:

def as_is_attr = {
            :primaryTitle;
            :titleType;
}

For integer fields loaded as strings use int_attr:

def int_attr = {
            :startYear; :endYear; :numVotes; :runtimeMinutes;
}

For float (decimals) use float_attr:

def float_attr = {
            :averageRating
}

For parsing date and datetime us date_attr and datetime_attr correspondingly (example not applicable to IMDB):

def datetime_attr = {
            (:CreationDate, "y-m-dTH:M:S.sss");
            (:LastAccessDate, "y-m-dTH:M:S.sss");
}

More types could be supported in the future.

Finally, use attr_alias_map to rename attributes (if necessary):

def attr_alias_map = {
            (:nconst, :id);
        }

Finally, we can create data model by mapping CSV file:

with se_csv use parse_attributes

module imdb_data

    // Title entity data
    def title:id = transpose[create_entity:title_from_id]
    def title(attr, e, val) = parse_attributes[title:id, title_csv, imdb_meta:title](attr, e, val)

end

Spring REST API

TBD...

Main and Big Ideas

Resarch Upstream that results in Product Downstream - no exceptions and identified and planed from the beginning:

• Teams like DS team should be "research"-focused upstrem and "product"-bound downstream. It means that they start with and do research/dev that should always result in identified and defined products or product enhancements.

Back to Shesterkin. He apparently "starred" in the exhibition game where #WarCrimes Putin scored 8 goals against him (the game took place in May 2019 before full scale #UkraineRussiaWar): https://twitter.com/eddie_p_412/status/1523851402103111680?s=20&t=c6OjwKxXmgbTw9SRU3eH1w 3/4