Note 1: All the of this presentation is published in this [repository](). You will find a lot of folders and information, probably part of a blog series.

Note 3: This is something that is related for HIPAA compliant.

## KMS/RDS

The POC on this article was developed before the releasing of the Key Management service for RDS.

I totally discourage to use the current approach for encrypting data. Use REST.

## Introduction

I’ve been dealing with an issue that came into my desktop from people of the community, regarding RDS and HIPAA rules. There was a confusing scenario whether PostgreSQL was using FTS and encryption on RDS. There are a lot of details regarding the architecture, however I think it won’t be necessary to dig into very deeply to understand the basics of the present article moto.

HIPAA rules are complex and if you need to deal with them, you’ll probably need to go through a careful read.

tl;dr? they tell us to store data encrypted on servers that are not in the premises. And that’s the case of RDS. However, all the communications are encrypted using SSL protocol, but is not enough to compliant with HIPAA rules.

CPU resources in RDS are expensive and not stable sometimes, which makes encryption and FTS features not very well suited for this kind of service. I not saying that you can’t implement them, just keep in mind that a standard CPU against vCPU could have a lot difference. If you want to benchmark your local CPU against RDS vCPU, you can run the following query inside psql on both instances:

\o /dev/null
\timing
SELECT convert_from(
pgp_sym_decrypt_bytea(
pgp_sym_encrypt_bytea('Text to be encrypted using pgp_sym_decrypt_bytea' || gen_random_uuid()::text::bytea,'key', 'compress-algo=2'),
'key'),
'SQL-ASCII')
FROM generate_series(1,10000);


There are a lot of things and functions you can combine from the pgcrypto package (you will see that the repository contemplates all of them). I will try to post another blog post regarding this kind of benchmarks. In the meantime, this query should be enough to have a rough idea of the performance difference between RDS instance vCPU and your server CPUs.

## Architecture basics

For this POC we are going to store FTS and GPG keys locally, in a simple PostgreSQL instance and, using a trigger, encrypt and upload transparently to RDS using the standard FDW (Foreign Data Wrappers).

Have in mind that RDS communication is already encrypted via SSL when data flows between server/client. It’s important to clarify this, to avoid confusions between communication encryption and storing data encrypted.

The simple trigger will split the unencrypted data between a local table storing in a tsvector column (jsonb in the TODO), it will encrypt and push the encrypted data into RDS using FDW (the standard postgres_fdw package).

A simple flight view of the idea can be observed in the image bellow.

Source

## RDS structure and mirrored local structure with FDW

RDS instance schema structure contains a parent table , a partitioning trigger and its trigger:

CREATE SCHEMA enc_schema;

SET search_path TO enc_schema;

-- Encrpting locally, that's why we don't need to reference the key here.
CREATE TABLE enc_schema.__person__pgp
(
id bigint,
source varchar(8),
partial_ssn varchar(4), -- Non encrypted field for other fast search purposes
ssn bytea,
keyid varchar(16),
fname bytea,
lname bytea,
description bytea,
auth_drugs bytea, 		-- This is an encrypted text vector
patology bytea,
PRIMARY KEY(id,source)
);

CREATE INDEX ON enc_schema.__person__pgp (partial_ssn);

CREATE OR REPLACE FUNCTION basic_ins_trig() RETURNS trigger LANGUAGE plpgsql AS $basic_ins_trig$
DECLARE
compTable text :=  TG_RELID::regclass::text ;
childTable text := compTable || '_' || NEW.source ;
statement text :=  'INSERT INTO ' || childTable || ' SELECT (' || QUOTE_LITERAL(NEW) || '::'  || compTable ||  ').*' ;
createStmt text := 'CREATE TABLE ' || childTable  ||
'(CHECK (source =' || quote_literal(NEW.source) || ')) INHERITS (' || compTable || ')';
indexAdd1 text := 'CREATE INDEX ON ' || childTable || '(source,id)' ;
indexAdd2 text := 'CREATE INDEX ON ' || childTable || '(source,ssn)' ;
BEGIN
BEGIN
EXECUTE statement;
EXCEPTION
WHEN undefined_table THEN
EXECUTE createStmt;
EXECUTE statement;
END;
RETURN NULL;

END;

$basic_ins_trig$;

CREATE TRIGGER part_person_pgp BEFORE INSERT ON __person__pgp
FOR EACH ROW EXECUTE PROCEDURE basic_ins_trig() ;


We are not going to use the partial SSN column in the examples, but I found it very helpful to do RDS searches over encrypted data without fall into the need of decrypting in-the-fly the SSN. The last SSN’s 4-digits do not provide useful information if stolen.

Also, the magic of the multi-source data injection comes from the compound key using a bigint and a source tag.

Basically, you can think on the local nodes as proxies. You can insert data on every node, but the data will point to the RDS instance.

If you are planning to manage large amounts of data, you can partition the table on RDS, allowing a better organization for data management.

You will see no indexes over encrypted data

Local nodes structure:

CREATE DATABASE fts_proxy;  --  connect using \c fts_proxy on psql

-- The sauce
CREATE EXTENSION postgres_fdw;
CREATE EXTENSION pgcrypto;

CREATE SERVER RDS_server
FOREIGN DATA WRAPPER postgres_fdw
OPTIONS (host 'dbtest1.chuxsnuhtvgl.us-east-1.rds.amazonaws.com', port '5432', dbname 'dbtest');

CREATE USER MAPPING FOR postgres
SERVER RDS_server

CREATE FOREIGN TABLE __person__pgp_RDS
(
id bigint,
source varchar(8),
partial_ssn varchar(4), -- Non encrypted field for other fast search purposes
ssn bytea,
keyid varchar(16),
fname bytea,
lname bytea,
description bytea,
auth_drugs bytea, -- This is an encrypted text vector
patology bytea
)
SERVER RDS_server
OPTIONS (schema_name 'enc_schema', table_name '__person__pgp');


Same table. Everytime we want to deal with the RDS table, we are going to do so using the __person__pgp_RDS table, which is just a mapping table. We can query this table as any other usual table.

For testing purposes, I also created a table with the same structure as the above with __person_rds_RDS_URE table name and added the use_remote_estimate 'true' option. When enabled, postgres_fdw obtains the row count and estimates from the remote server.

## Inserting keys locally

Just to avoid an extended article, I will skip the GPG key creation commands here. Please follow the instructions on the link at the referece section about keys.

We can insert they keys in several ways, but I found very convenient to use psql features to do so. Once the keys are in place you can use \lo_import command:

postgres=# \lo_import /var/lib/postgresql/9.4/main/private.key
lo_import 33583
postgres=# \lo_import /var/lib/postgresql/9.4/main/public.key
lo_import 33584


The next steps are very straightforward. In a real scenario, you won’t probably want to upload private keys into the table, just for practical purposes of this article I’m going to do so (only for decrypt data in the SELECT query).

pgp_key_id will return the same key no matter if you use private or public key.

CREATE TABLE keys (
keyid varchar(16) PRIMARY KEY,
pub bytea,
priv bytea
);

INSERT INTO keys VALUES ( pgp_key_id(lo_get(33583)) ,lo_get(33584), lo_get(33583));


## Splitting data to FTS, encrypt and push into RDS

Now, here is when the tricky part starts. We are going to achieve some functionalities:

• We are going to simulate routing using inheritance on the FTS records. That will allow us to split data as we want and, replicate using Logical Decoding feature between the nodes. I won’t include this on the current article just to avoid it to be extense.
• We are going to encrypt using the key that we select on the insert query. If you want a key per table basis, you will find easier to hardcode the key id on the _func_get_FTS_encrypt_and_push_to_RDS.
• Once the records are encrypted, the function will insert those records to the foreign table (RDS).
• When querying the FTS table, we will be able to determine the source (something like the routing technique, you will find this familiar if you played with ElasticSearch). That allow us to make the FTS search transparent to the application, pointing always to the parent table. :dogewow:

Isn’t Postgres cool? :o

### FTS table structures

-- Parent table
CREATE TABLE local_search (
id bigint PRIMARY KEY,
_FTS tsvector
);
CREATE INDEX fts_index ON local_search USING GIST(_FTS);

-- Child table, suffix local_search_<source>

CREATE TABLE local_search_host1 () INHERITS (local_search);
CREATE INDEX fts_index_host1 ON local_search_host1 USING GIST(_FTS);


Doing this, you avoid to have a column with a constant value in the table, consuming unnecessary space. You can have with this method, different names and tables accross the cluster, but always using the same query against local_search. You can map/reduce the data if you want to across the nodes, with the very same query.

Is not necessary to only have 1 source or route per node. The only requirement for this is to have different routes per node (combining source and route could increase complexity, however is possible).

## Main code

CREATE SEQUENCE global_seq INCREMENT BY 1 MINVALUE 1 NO MAXVALUE;

CREATE TABLE __person__pgp_map
(
keyid varchar(16),
source varchar(8),
ssn bigint,
fname text,
lname text,
description text,
auth_drugs text[], -- This is an encrypted text vector
patology text
);

CREATE OR REPLACE FUNCTION _func_get_FTS_encrypt_and_push_to_RDS() RETURNS "trigger" AS $$DECLARE secret bytea; RDS_MAP __person__pgp_RDS%ROWTYPE; FTS_MAP local_search%ROWTYPE; BEGIN SELECT pub INTO secret FROM keys WHERE keyid = NEW.keyid; RDS_MAP.source := NEW.source; RDS_MAP.fname := pgp_pub_encrypt(NEW.fname, secret); RDS_MAP.lname := pgp_pub_encrypt(NEW.lname, secret); RDS_MAP.auth_drugs := pgp_pub_encrypt(NEW.auth_drugs::text, secret); RDS_MAP.description := pgp_pub_encrypt(NEW.description, secret); RDS_MAP.patology := pgp_pub_encrypt(NEW.patology, secret); RDS_MAP.ssn := pgp_pub_encrypt(NEW.ssn::text, secret); RDS_MAP.partial_ssn := right( (NEW.ssn)::text,4); RDS_MAP.id := nextval('global_seq'::regclass); RDS_MAP.keyid := NEW.keyid; FTS_MAP.id := RDS_MAP.id; FTS_MAP._FTS := (setweight(to_tsvector(NEW.fname) , 'B' ) || setweight(to_tsvector(NEW.lname), 'A') || setweight(to_tsvector(NEW.description), 'C') || setweight(to_tsvector(NEW.auth_drugs::text), 'C') || setweight(to_tsvector(NEW.patology), 'D') ) ; -- Both tables contain same id,source INSERT INTO __person__pgp_RDS SELECT (RDS_MAP.*); EXECUTE 'INSERT INTO local_search_' || NEW.source || ' SELECT (' || quote_literal(FTS_MAP) || '::local_search).* '; RETURN NULL; END;$$
LANGUAGE plpgsql;

CREATE TRIGGER trigger_befInsRow_name_FTS
BEFORE INSERT ON __person__pgp_map
FOR EACH ROW
EXECUTE PROCEDURE _func_get_FTS_encrypt_and_push_to_RDS();


This functions does everything. It inserts the data on RDS and split the data on the corresponding FTS child table. For performance purposes, I didn’t want to catch exceptions at insert time (if the child table does not exists, i.e.), but you can also add this feature with an exception block as follows:

   BEGIN
EXECUTE 'INSERT INTO local_search_' || NEW.source || ' SELECT (' ||  quote_literal(FTS_MAP) || '::local_search).* ';
EXCEPTION WHEN undefined_table THEN
EXECUTE 'CREATE TABLE local_search_' || NEW.source || '() INHERITS local_search';
END;


The same can be done over the foreign table. More info in “Class HV — Foreign Data Wrapper Error (SQL/MED)” (HV00R -fdw_table_not_found).

Check “Appendix A. PostgreSQL Error Codes” on the official manual for references about error codes.

### Inserting data

At insertion time, we are going to push data through a mapping table. The reason for this is that all the encrypted data is stored in bytea datatype, and we want to have clear queries instead.

A random data query will look as:

INSERT INTO __person__pgp_map
SELECT
'host1',  -- source: host1
-- You can do this better by grabbing this data from a persistent
-- location
'76CDA76B5C1EA9AB',
round(random()*1000000000),
('{Romulo,Ricardo,Romina,Fabricio,Francisca,Noa,Laura,Priscila,Tiziana,Ana,Horacio,Tim,Mario}'::text[])[round(random()*12+1)],
('{Perez,Ortigoza,Tucci,Smith,Fernandez,Samuel,Veloso,Guevara,Calvo,Cantina,Casas,Korn,Rodriguez,Ike,Baldo,Vespi}'::text[])[round(random()*15+1)],
('{some,random,text,goes,here}'::text[])[round(random()*5+1)] ,
get_drugs_random(round(random()*10)::int),
('{Anotia,Appendicitis,Apraxia,Argyria,Arthritis,Asthma,Astigmatism,Atherosclerosis,Athetosis,Atrophy,Abscess,Influenza,Melanoma}'::text[])[round(random()*12+1)]
FROM generate_series(1,50) ;


Did you see the inner comment? Well, probably you want to split by customer or any other alias. I’m using this ugly harcoded text just to avoid a long article.

Also, if you want to avoid harcoding as much as posible, you can consider to use a function that returns the host name or routing tag.

### Querying the data

We are almost done! Now we can do some queries. Here are some examples:

Limiting the matches:

# SELECT convert_from(pgp_pub_decrypt(ssn::text::bytea, ks.priv,''::text)::bytea,'SQL_ASCII'::name)
# FROM __person__pgp_rds as rds JOIN
#       keys ks USING (keyid)
# WHERE rds.id IN (
#                select id
#                from local_search
#                where to_tsquery('Asthma | Athetosis') @@ _fts LIMIT 5)
#   AND rds.source = 'host1';

source | convert_from
--------+--------------
host1  | 563588056
(1 row)



All the matches and double check from were the data came from:

# SELECT ls.tableoid::regclass, rds.source,
#        convert_from(pgp_pub_decrypt(ssn::text::bytea, ks.priv,''::text)::bytea,'SQL_ASCII'::name)
# FROM local_search ls JOIN
#     __person__pgp_rds as rds USING (id),
#     keys ks
# WHERE to_tsquery('Asthma | Athetosis') @@ ls._fts;

tableoid      | source | convert_from
-------------------+--------+--------------
local_search_host1 | host1  | 563588056
(1 row)


And, we can’t finish the article without showing how to use the ranking (did you see those setweight functions used in the function? You got it!):

#  SELECT rds.id,
#  convert_from(pgp_pub_decrypt(fname::bytea, ks.priv,''::text)::bytea,'SQL_ASCII'::name),
#  convert_from(pgp_pub_decrypt(lname::bytea, ks.priv,''::text)::bytea,'SQL_ASCII'::name),
#  ts_rank( ls._FTS, query ) as rank
#    FROM local_search ls JOIN
#         __person__pgp_rds as rds ON (rds.id = ls.id AND rds.source = 'host1') JOIN
#         keys ks USING (keyid),
#         to_tsquery('Mario | Casas | (Casas:*A & Mario:*B) ') query
#    WHERE
#        ls._FTS  @@ query
#    ORDER BY rank DESC;

id | convert_from | convert_from |   rank
----+--------------+--------------+----------
43 | Mario        | Casas        | 0.425549
61 | Ana          | Casas        | 0.303964
66 | Horacio      | Casas        | 0.303964
(3 rows)


Remember, think that this query is doing FTS, decryption and ranking in just one query, over a local and a remote server. You can’t say that PostgreSQL isn’t hipster enough!

I can’t continue the article without showing the query plan executed by the local host (using buffers, analyze and verbose options).

EXPLAIN (buffers,verbose,analyze) SELECT rds.id,
convert_from(pgp_pub_decrypt(fname::bytea, ks.priv,''::text)::bytea,'SQL_ASCII'::name),
convert_from(pgp_pub_decrypt(lname::bytea, ks.priv,''::text)::bytea,'SQL_ASCII'::name),
ts_rank( ls._FTS, query ) as rank
FROM local_search ls JOIN
__person__pgp_rds as rds ON (rds.id = ls.id AND rds.source = 'host1') JOIN
keys ks USING (keyid),
to_tsquery('Mario | Casas | (Casas:*A & Mario:*B) ') query
WHERE
ls._FTS  @@ query
ORDER BY rank DESC;

....
->  Materialize  (cost=100.00..117.09 rows=3 width=122) (actual time=62.946..62.971 rows=50 loops=9)
Output: rds.id, rds.fname, rds.lname, rds.keyid
->  Foreign Scan on public.__person__pgp_rds rds  (cost=100.00..117.07 rows=3 width=122) (actual time=566.495..566.520 rows=50 loops=1)
Output: rds.id, rds.fname, rds.lname, rds.keyid
Remote SQL: SELECT id, keyid, fname, lname FROM enc_schema.__person__pgp WHERE ((source = 'host1'::text))
...
Planning time: 4.931 ms
Execution time: 2115.919 ms
(45 rows)



From the above Query Plan extract, we can see that the partitioning at RDS is transparent for the query. The execution node in charge of extracting data from the RDS is the Foreign Scan, which also provides the query executed remotely.

Wait a minute. Looks like the remote SQL is somehow dangerous to execute. It is not using the id! There is a reason for that, and its related on how postgres gather the foreign table statistics. If I use the remote estimations we can see how the remote SQL changes in the Query Plan:

 EXPLAIN (ANALYZE, VERBOSE, BUFFERS) SELECT rds.id,
convert_from(pgp_pub_decrypt(fname::bytea, ks.priv,''::text)::bytea,'SQL_ASCII'::name),
convert_from(pgp_pub_decrypt(lname::bytea, ks.priv,''::text)::bytea,'SQL_ASCII'::name),
ts_rank( ls._FTS, query ) as rank
FROM local_search ls,  __person__pgp_rds_URE  rds  JOIN
keys ks USING (keyid),
to_tsquery('Mario | Casas | (Casas:*A & Mario:*B) ') query
WHERE
rds.id = ls.id
AND rds.source = 'host1'
AND
ls._FTS  @@ query
ORDER BY rank DESC;


Query Plan (Foreign Scan execution node):

...
->  Foreign Scan on public.__person__pgp_rds_ure rds  (cost=100.01..108.21 rows=2 width=1018) (actual time=250.334..250.336 rows=1 loops=31)
Output: rds.id, rds.source, rds.partial_ssn, rds.ssn, rds.keyid, rds.fname, rds.lname, rds.description, rds.auth_drugs, rds.patology
Remote SQL: SELECT id, keyid, fname, lname FROM enc_schema.__person__pgp WHERE ((source = 'host1'::text)) AND (($1::bigint = id)) ...  Foreign tables also need the local statistics to be updated. In the next examples there are 3 queries: using the use_remote_estimate, without previous ANALYZE and without use_remote_estimate and a query using the local estimations (__person_pgp_rds) after issuing ANALYZE and without URE. fts_proxy=# \o /dev/null fts_proxy=# SELECT rds.id, convert_from(pgp_pub_decrypt(fname::bytea, ks.priv,''::text)::bytea,'SQL_ASCII'::name), convert_from(pgp_pub_decrypt(lname::bytea, ks.priv,''::text)::bytea,'SQL_ASCII'::name), ts_rank( ls._FTS, query ) as rank FROM local_search ls, __person__pgp_rds_URE rds JOIN keys ks USING (keyid), to_tsquery('Mario | Casas | (Casas:*A & Mario:*B) ') query WHERE rds.id = ls.id AND rds.source = 'host1' AND ls._FTS @@ query ORDER BY rank DESC; Time: 12299,691 ms fts_proxy=# SELECT rds.id, convert_from(pgp_pub_decrypt(fname::bytea, ks.priv,''::text)::bytea,'SQL_ASCII'::name), convert_from(pgp_pub_decrypt(lname::bytea, ks.priv,''::text)::bytea,'SQL_ASCII'::name), ts_rank( ls._FTS, query ) as rank FROM local_search ls, __person__pgp_rds rds JOIN keys ks USING (keyid), to_tsquery('Mario | Casas | (Casas:*A & Mario:*B) ') query WHERE rds.id = ls.id AND rds.source = 'host1' AND ls._FTS @@ query ORDER BY rank DESC; Time: 20249,719 ms -- AFTER ANALYZE on the FOREIGN TABLE __person_pgp_rds (in the local server) Time: 1656,912 ms  After analyzing both foreign tables , the execution time difference was calculated at 11% in favor of using local estimations. NOTE about UPDATES: it is necessary to code the UPDATE trigger also, in order to decrypt , modify and re-encrypt the data. ### Json/jsonb datatype is here to help You can collapse all the data and use json datatype on the mapping and foreign table, allowing you to avoid the pain of pointing and decrypting data per column basis. Put all the encrypted columns in a bytea column on RDS. The mapping table will look as follows: CREATE TABLE __person__pgp_map ( keyid varchar(16), source varchar(8), ssn bigint, data jsonb );  At insert time, just use a json column instead per column basis. Keep in mind that you will need to deal within the json contents. I found using this easier for insert, but the FTS needs some clean up to avoid insert column names in the _fts field at local_search tables. Also, for updates, the jsonb datatype will need extra work when extracting attributes. ## Additional functions used here In the insert statement above, you will see a user defined function that gets a random length vector of drugs. It is implemented using the following code: CREATE TABLE drugsList ( id serial PRIMARY KEY, drugName text); INSERT INTO drugsList(drugName) SELECT p.nameD FROM regexp_split_to_table( 'Acetaminophen Adderall Alprazolam Amitriptyline Amlodipine Amoxicillin Ativan Atorvastatin Azithromycin Ciprofloxacin Citalopram Clindamycin Clonazepam Codeine Cyclobenzaprine Cymbalta Doxycycline Gabapentin Hydrochlorothiazide Ibuprofen Lexapro Lisinopril Loratadine Lorazepam Losartan Lyrica Meloxicam Metformin Metoprolol Naproxen Omeprazole Oxycodone Pantoprazole Prednisone Tramadol Trazodone Viagra Wellbutrin Xanax Zoloft', '\n') p(nameD); CREATE OR REPLACE FUNCTION get_drugs_random(int) RETURNS text[] AS$BODY$WITH rdrugs(dname) AS ( SELECT drugName FROM drugsList p ORDER BY random() LIMIT$1
)
SELECT array_agg(dname) FROM rdrugs ;
$BODY$
LANGUAGE 'sql' VOLATILE;


## References

A very awesome tutorial about FTS for PostgreSQL can be found here.

Source for drugs list

Source for diseases

Getting started with GPG keys

AWS command line tool

Discussion in the community mailing lis here