Try all datasets in a single SQL table, plug-and-play!
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README.md

SQL dataset unifier

Try all datasets in a single PostgreSQL table, plug-and-play! Load and manage all your FrictionLessData tabular packages (CSV datasets) with SQL.

Load in a single big table, where each CSV line is converted into a tabular JSON array. In PostgreSQL 9.5+ the best way to digital preservation is the JSONb datatype, so the big table of datasets is:

CREATE TABLE dataset.big (
  id bigserial not null primary key,  -- control for (rare) splitted datasets
  source int NOT NULL REFERENCES dataset.meta(id) ON DELETE CASCADE, -- Controls and all metadata.
  j JSONb NOT NULL, -- Dataset contents goes here!
);

Each line of all CSV files is loaded into a JSONb array: CSV datatype is preserved and data representation is the most efficient and compressed — with fast access, indexation and full flexibility of JSONb functions and operators. The most important to manage lines of tabular data is to split by jsonb_array_elements() function or to join by jsonb_agg() function (see disk-usage and performance benchmarks).

The framework also offers usual relational data access by SQL-VIEW, generated automatically (!) and casting original datatypes to consistent SQL datatypes, to build joins and other complex SQL expressions from the preserved datasets. Export and import, many formats, also easy.

Simplest use (demo)

If there are no special database, create trydatasets database. If there are no special user, etc. you can use the URI-connection postgresql://postgres:postgres@localhost/trydatasets as at default conf.json.

git clone https://github.com/datasets-br/try-sql-datasets.git
cd try-sql-datasets
php src/php/pack2sql.php # generates cache from default conf.json
sh src/cache/make.sh

Done! Try eg. with psql URI (as connection comment above) some queries:

  • a summary of all saved datasets: SELECT * FROM dataset.vmeta_summary;
  • a complete list of all fields: SELECT * FROM dataset.vmeta_fields;
  • all brasilian states at CSV file: SELECT * FROM tmpcsv4_br_state_codes;
  • same dataset in the database as a big table of JSON arrays: SELECT c FROM dataset.big WHERE dataset.meta_id('br_state_codes');
  • same again, but using the standard SQL VIEW create for simplify dataset.big access: SELECT * FROM vw_br_state_codes;

For v*meta_* summary functions see also Appendix with JSON output and other examples.

For handling datasets in complex queries, a typical JOIN with two datasets: ietf_language_tags and country_codes,

SELECT i.*, c.official_name_en
FROM dataset.vw_ietf_language_tags i INNER JOIN dataset.vw_country_codes c
  ON c.iso3166_1_alpha_2=i.territory;

All tested with PostgreSQL v9.6 in an UBUNTU 16 LTS. CSVkit v1.0.2.

Configurating

Change the default conf.json to your needs, pointing it to datasets of github.com/datasets or datasets.ok.org.br. Example: all CSVs of country-codes, of city-codes and the main CSV of state-codes,

{
   "db":"postgresql://postgres:postgres@localhost:5432/trydatasets",
   "github.com":{
        "datasets/country-codes":null,
        "datasets-br/state-codes":"br-state-codes",
        "datasets-br/city-codes":null
   },
   "local-csv":{
     "test2017":{
       "separator":";",
       "folder":"/home/user/mytests"
     },
     "otherTests":"/home/user/myOthertests"
   },
   "useBig":true, "useIDX":false, "useRename":true
}

The use* flags are for create or not the big table dataset.Big; for nominate temporary tables by an index or with real dataset names; and, for nominate fields, using or not an rename rule (to avoid quotes in SQL commands).

To use local folder instead Github repository, add the path as local. For instance:

"github.com":{ "...":"..." },
"local":{"/home/user/sandbox/cbh-codes":null},

When there are no datapackage.json descriptor in the folder, use local-csv as the example above (JSON with folder and separator fields). You can also to point each CSV file directly, example: "local-csv":["../test12.csv", "/tmp/t.csv"].

After edit conf.json, run the pack2sql and again the sequence of init commands (supposing at root of the git),

php src/php/pack2sql.php # at each conf edit
rm -r /tmp/tmpcsv        # only when need to rebuild from new data in the Web
sh src/cache/make.sh     # rebuilds CSV files by wget and rebuilds SQL

Using with SQL and useBig

All CSV lines of all CSV files was loaded in JSON arrays, at table dataset.big.

All loaded foregin CSV tables are named tmpcsv_*. List the * names with SELECT * FROM dataset.vmeta_summary.
You can drop all server interfaces by DROP SERVER csv_files CASCADE, without impact in the dataset schema.

To generate full dataset schema for an external database (to avoid to read CSV or local FOREGIN TABLE), try something like pg_dump -n dataset postgresql://postgres:postgres@localhost:5432/trydatasets > /tmp/dump_n_dataset.sql.

Only shell and SQL

There are no external library or language dependences. Only the script generator is a language-dependent module (eg. PHP script), all installation scripts are language-agnostic: see  src/*.sql and src/cache, you need only shell and psql (or a SQL-migration tool) to create the dataset SQL schema with the configurated datasets.

Exporting you datasets as CSV or JSON

The original datasets and your new (SQL-builded) datasets can be exported in many formats, main ones are CSV and JSON.

Lets use summarizations (dataset.vmeta_summary and dataset.vmeta_fields) as example for CSV and JSON outputs.

SQL COPY TO

The easyest way is to export to /tmp/ folder by COPY t TO '/tmp/test.csv' CSV HEADER usual command. As all dataset.big fragments are SQL-VIEWs, we need to express it by a SELECT. For JSON is the same, need only to ommit the CSV option:

-- export vmeta_summary as CSV:
 COPY (SELECT * FROM dataset.vmeta_summary) TO '/tmp/meta_summary.csv' CSV HEADER;
-- export same content as JSON-array:
 COPY (SELECT * FROM dataset.vjmeta_summary) TO '/tmp/meta_summary.json';

-- export all structured vmeta_fields as JSON-array:
 COPY (SELECT jsonb_agg(jmeta_fields) FROM dataset.vjmeta_fields) TO '/tmp/meta_fields.json';

To pretty-JSON you need some workaround after export SELECT jsonb_pretty(x), because the lines are encoded by explicit "\n"...

  1. COPY fragment that you want. Eg. COPY (SELECT jsonb_pretty(jsonb_agg(jmeta_fields)) FROM dataset.vjmeta_fields WHERE dataset_id IN (1,3)) TO '/tmp/meta_fields_1and3.json'

  2. Convert the \n to real line-breaks, by sed 's/\\n/\n/g' < /tmp/meta_fields_1and3.json > myFields.json

psql

With the psql command you can explore powerful terminal commands, to avoid /tmp intermediary folder (use relative path!) or use in pipe to remote database or remote files, gzip, etc.

psql -h remotehost -d remote_mydb -U myuser -c " \
   COPY (SELECT * FROM dataset.vjmeta_summary) TO STDOUT \
   " > ./relative_path/file.json

Internal psql commands (as \t \a \o) are also easy, see this tips.

Collabore

  • development: the algorithm is simple, can be any language. The reference-implamentation is PHP. See /src/_language_ folder, at src.
  • using: add issues here.

Other motivations: a comment about non-SQL tools like CSVkit, in its documentation, csvkit sec.3,

"Sometimes (almost always), the command-line isn’t enough. It would be crazy to try to do all your analysis using command-line tools. Often times, the correct tool for data analysis is SQL".