The trino-by-example from skhatri

Overview

This is a recipe to create a Presto/Trino cluster with hive.

Index

Build Images
Download Client
Certificates
Configure Environment/Secrets
Test Trino Connectivity
Setup S3 environment
S3 Credentials
Create Table in Hive with S3
Queries using Hive
Queries using Trino
Access Control
Querying with Superset
Running with Envoy

Build Images

If you do want to build your own images, update docker-compose.yaml to enable image: for hive and trino

make build will build trino image and make build-hive will build a hive image from scratch. Note hive/Dockerfile relies on hive and hadoop binary to be available locally to save bandwidth for local builds. So you will have to download it once and reuse it.

Download client

curl -s -o trino https://repo1.maven.org/maven2/io/trino/trino-cli/418/trino-cli-418-executable.jar
chmod +x trino

Certificates

Generate keystore and truststore

keytool -genkeypair -alias trino -keyalg RSA -keystore certs/keystore.jks \
-dname "CN=coordinator, OU=datalake, O=dataco, L=Sydney, ST=NSW, C=AU" \
-ext san=dns:coordinator,dns:coordinator.presto,dns:coordinator.presto.svc,dns:coordinator.presto.svc.cluster.local,dns:coordinator-headless,dns:coordinator-headless.presto,dns:coordinator-headless.presto.svc,dns:coordinator-headless.presto.svc.cluster.local,dns:localhost,dns:trino-proxy,ip:127.0.0.1,ip:192.168.64.5,ip:192.168.64.6 \
-storepass password

keytool -exportcert -file certs/trino.cer -alias trino -keystore certs/keystore.jks -storepass password

keytool -import -v -trustcacerts -alias trino_trust -file certs/trino.cer -keystore certs/truststore.jks -storepass password -keypass password -noprompt


keytool -keystore certs/keystore.jks -exportcert -alias trino -storepass password| openssl x509 -inform der -text

keytool -importkeystore -srckeystore certs/keystore.jks -destkeystore certs/trino.p12 -srcstoretype jks -deststoretype pkcs12 -srcstorepass password -deststorepass password 

openssl pkcs12 -in certs/trino.p12 -out certs/trino.pem

openssl x509 -in certs/trino.cer -inform DER -out certs/trino.crt

Configure Environment/Secrets

Let's start presto coordinator, presto worker, hive, postgres using docker-compose. Before starting it, please perform the following

cp .env.template .env

and put the secrets in .env file

Run ./env.sh to substitute S3 and Postgres password in hive-site.xml

It is highly advisable that you update your /etc/hosts or equivalent file with the following host entries so we can use same DNS names inside docker as well as in your cli.

/etc/hosts:

127.0.0.1	coordinator worker-1 worker-0 trino-proxy
127.0.0.1	postgres

docker-compose up can be run using make up Check the progress using make ps and once all containers are up, navigate to https://localhost:8443/ui/ with credentials admin/password to view the presto UI.

Test Trino Connectivity

Run make trino with password as "password" to login to trino using the trino executable jar. Here issue command like show catalogs; to see all available catalogs for query.

show catalogs;
show schemas in tpch;
show tables in tpch.sf1;
select * from tpch.sf1.nation;

The same query can be run through rest URI

curl -k https://coordinator:8443/v1/statement/ \
--header "Authorization: Basic YWRtaW46cGFzc3dvcmQ=" \
--header "X-Trino-User: admin" \
--header "X-Trino-Schema: sf1" \
--header "X-Trino-Source: somesource" \
--header "X-Trino-Time-Zone: UTC" \
--header "X-Trino-Catalog: tpch" \
--header "User-Agent: trino-cli" \
--data "select * from nation"

Setup S3 environment

create a s3 bucket for this project and upload test data to s3 bucket

replace endpoint-url if not running minio at all.

while read line; do if [[ ! "$line" =~ ^# ]]; then export $line; fi; done < .env;
AWS_ACCESS_KEY_ID=${STORE_KEY} AWS_SECRET_ACCESS_KEY=${STORE_SECRET} \
aws s3 --endpoint-url http://localhost:9005 mb s3://my-trino-dataset

I used by google fit app data for this

AWS_ACCESS_KEY_ID=${STORE_KEY} AWS_SECRET_ACCESS_KEY=${STORE_SECRET} \
aws s3 --endpoint-url http://localhost:9005 cp hive/sampledata.csv s3://my-trino-dataset/data/fit/load_date=2021-03-06/

also upload sample finance data to another slice in the same bucket

AWS_ACCESS_KEY_ID=${STORE_KEY} AWS_SECRET_ACCESS_KEY=${STORE_SECRET} \
aws s3 --endpoint-url http://localhost:9005 cp --recursive hive/output s3://my-trino-dataset/data/finance/output

Let's list the data in object storage to verify that the upload is successful

AWS_ACCESS_KEY_ID=${STORE_KEY} AWS_SECRET_ACCESS_KEY=${STORE_SECRET} \
aws s3 --endpoint-url http://localhost:9005 ls s3://my-trino-dataset/data --recursive

S3 Credentials

In order to provide maximum flexibility and avoid secret sprawl, we are implementing a custom credential provider and reusing it for both Hive and Trino usage. This ensures our hive-site.xml and trino hive properties do not need to have sensitive information.

To avoid conflicts with environment variables and the default behaviour, we are using the following four environment variables to determine what our secret strategy is going to be. We could also provide these as XML string property in hive resource xml file.

        String accessKey = System.getenv("STORE_KEY");
        String secretKey = System.getenv("STORE_SECRET");
        String identityFile = System.getenv("STORE_TOKEN_FILE");
        String roleArn = System.getenv("STORE_ROLE_ARN");

Refer to CredentialsFactory.java in hive-authz project to view/change the credentials derivation strategy.

Create Table in Hive with S3

Next, login to hive and create the activity table. Register a new partition also

make hive-cli

#set bucket name as variable

set hivevar:bucket_name=my-trino-dataset;
CREATE DATABASE fitness;
use fitness;

CREATE EXTERNAL TABLE activity (
    activity_date date,
    average_weight string,
    max_weight string,
    min_weight string,
    calories float,
    heart_points float,
    heart_minutes float,
    low_latitude float,
    low_longitude float,
    high_latitude float,
    high_longitude float,
    step_count int,
    distance float,
    average_speed float,
    max_speed float,
    min_speed float,
    move_minutes_count int,
    cycling_duration float,
    inactive_duration float,
    walking_duration float,
    running_duration float
) PARTITIONED BY (load_date date)
ROW FORMAT DELIMITED FIELDS TERMINATED BY ','
LOCATION 's3a://${hivevar:bucket_name}/data/fit'
TBLPROPERTIES ("skip.header.line.count"="1");

ALTER TABLE activity
ADD PARTITION (load_date='2021-03-06') LOCATION 's3a://${hivevar:bucket_name}/data/fit/load_date=2021-03-06';

Create Delta Lake Table

CREATE DATABASE finance;


DROP TABLE IF EXISTS finance.activity;

#Using spark delta generated manifest
CREATE EXTERNAL TABLE finance.activity(
    account string,
    txn_id string,
    merchant string,
    category string,
    last_updated timestamp,
    deleted boolean,
    txn_date date,
    amount float
) partitioned by (version date)
ROW FORMAT SERDE 'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe'
STORED AS INPUTFORMAT 'org.apache.hadoop.hive.ql.io.SymlinkTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION 's3a://${hivevar:bucket_name}/data/finance/output/activity/_symlink_format_manifest/';

MSCK REPAIR TABLE finance.activity;

DROP TABLE IF EXISTS finance.activity_snapshot;

CREATE EXTERNAL TABLE finance.activity_snapshot(
    account string,
    txn_id string,
    merchant string,
    category string,
    last_updated timestamp,
    deleted boolean,
    txn_date date,
    amount float
) partitioned by (version date)
ROW FORMAT SERDE 'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe'
STORED AS INPUTFORMAT 'org.apache.hadoop.hive.ql.io.SymlinkTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION 's3a://${hivevar:bucket_name}/data/finance/output/activity/_delta_manifest/';

MSCK REPAIR TABLE finance.activity_snapshot;

Queries using Hive

Just using hive, we can do the following queries as well.

How much have I walked since I installed the fit app?

use fitness;
select sum(step_count) as steps, sum(distance)/1000 as distance_in_kms from activity;

Monthly activity summary

select year(activity_date), month(activity_date), sum(heart_points) as heart_pt, sum(step_count) as steps, sum(distance)/1000 as km
from activity
group by year(activity_date), month(activity_date);

Queries using Trino

make trino

show catalogs;
show schemas in hive;
show tables in hive.fitness;

select sum(step_count) as steps, sum(distance)/1000 as distance_in_kms from hive.fitness.activity;

use hive.fitness;
select year(activity_date) as year, month(activity_date) as month, sum(heart_points) as heart_pt, sum(step_count) as steps, sum(distance)/1000 as km
from activity
group by year(activity_date), month(activity_date);

Query Delta Data with Trino

View https://github.com/skhatri/spark-delta-by-example for relevant spark delta code There is pre delta 2.0 code and higher versions may have different API now.

Show available snapshots

select version, count(*) 
from hive.finance.activity_snapshot
group by version
order by version asc;

version	_col1
2021-03-02	15
2021-03-03	30
2021-03-05	45
2021-03-08	47
2021-03-09	50

There are 5 versions of the activity dataset for 5 date partitions. The last version has 50 records.

Show latest

select count(*)
from hive.finance.activity;

_col0
50

The activity table also contains the same number of records as the latest version. These records would be merged.

Find total number of activities by account

select account, count(*) as activity_count from hive.finance.activity
group by account;

As of a specific snapshot

As of version 2021-03-02, what was transaction id txn10 labelled as?

select * from hive.finance.activity_snapshot
where version=cast('2021-03-02' as date) and txn_id='txn10';

account	txn_id	merchant	category	last_updated	deleted	txn_date	amount	version
acc4	txn10	Prouds Jewellery	Jewellery	2021-03-01 13:00:00.000	false	2021-03-02	189.0	2021-03-02

(1 row)

select * from hive.finance.activity_snapshot
where version=cast('2021-03-09' as date) and txn_id='txn10';

account	txn_id	merchant	category	last_updated	deleted	txn_date	amount	version
acc4	txn10	Prouds Jewellery	Fashion	2021-03-07 13:00:00.000	false	2021-03-02	189.0	2021-03-09

Latest category

What is the latest category of transaction id txn10 and when was it last updated?

select * from hive.finance.activity
where txn_id='txn10';

account	txn_id	merchant	category	last_updated	deleted	txn_date	amount	version
acc4	txn10	Prouds Jewellery	Fashion	2021-03-07 13:00:00.000	false	2021-03-02	189.0	2021-03-02

Category Change over time

Acc5 bought something from Apple Store Sydney on 2021-03-05, how did the category for this transaction change over time?

select account, txn_date, category as latest_category, last_updated, txn_id
from hive.finance.activity
where account = 'acc5' and txn_date=cast('2021-03-05' as date) and merchant='Apple Store Sydney';

select account, txn_date, category as versioned_category, last_updated, txn_id
from hive.finance.activity_snapshot
where version=cast('2021-03-05' as date) and account = 'acc5' and txn_date=cast('2021-03-05' as date) and merchant='Apple Store Sydney';

It was initially labelled as Hardware and later it got changed to Phone.

Access Control

Let's create few users whose access will be configured in trino rules file.

htpasswd -C 10 -B -c security/passwords/password.db user1
htpasswd -C 10 -B security/passwords/password.db user2
htpasswd -C 10 -B security/passwords/password.db user3
htpasswd -C 10 -B security/passwords/password.db skhatri
htpasswd -C 10 -B security/passwords/password.db admin

Refer to security/rules/rules.json for configuration, the following table summaries the ACL by user.

User	Access
user1	finance.*,tpch,information_schema
user2	fitness.activity,tpch,information_schema
user3	finance.activity,tpch,information_schema
skhatri	finance., fitness.,tpch,information_schema
admin	*

Restart coordinator and worker-1 instances:

docker-compose stop worker-1
docker-compose stop coordinator
docker-compose start coordinator
docker-compose start worker-1

Querying as Users

Let's login as user1 and explore their privileges.

./trino --debug --user=user1 --password --truststore-path=./certs/truststore.jks --truststore-password=password --server https://localhost:8443

While the show catalogs; command lists the available catalogs. Listing schema in one of the catalogs like tpch will only show information_schema. If we try to retrieve customer data from tpch.sf1, it will throw exception:

select * from tpch.sf1.customer limit 2;

As user1 does not have access to tpch, the query will return error

Query 20220507_183600_00046_z589m failed: Access Denied: Cannot select from table tpch.sf1.customer
io.trino.spi.security.AccessDeniedException: Access Denied: Cannot select from table tpch.sf1.customer

In rules.json we have the following permission:

    {
      "user": "user1",
      "catalog": "hive",
      "schema": "finance",
      "table": ".*",
      "privileges": [
        "SELECT"
      ]
    }

We have granted user1 the access to query any table in schema finance of the catalog hive. Let's test this out.

show schemas in hive;

Schema
finance
information_schema

show tables in hive.finance;

So we can see finance schema for hive in the list of schema available here. While you can check the available tables with show tables in hive.finance, let's use our prior knowledge of hive finance tables and query activity table.

select * from hive.finance.activity limit 2;

Yes, we can retrieve the data as user1

account	txn_id	merchant	category	last_updated	deleted	txn_date	amount	version
acc2	txn36	Kathmandu Miranda	Clothing	2021-03-04 13:00:00.000	false	2021-03-05	69.95	2021-03-05
acc3	txn22	Optus Phone	Phone	2021-03-02 13:00:00.000	false	2021-03-03	40.0	2021-03-03

The rules.json can be reloaded periodically using security.refresh-period when using File system access control. If using this ACL in Kubernetes environment, it is possible to run a sidecar container along with coordinator which can fetch the file periodically from git or remote resource. Refresh option is available for access control file as well as the passwords file.

Refer to trino-ext-authz folder for a external authz plugin that is based on default file system access control.

Possible extension areas can be calling Open Policy Agent server from the external authz plugin to determine or downloading rules json from a remote resource and caching it. A new yaml DSL can be maintained to keep rules simpler.

Querying with Superset

Setup a database in Superset using the following URL and connect params

Loging to http://localhost:9000/ with admin/admin

Go to the screen to add a new database http://localhost:9000/databaseview/add and configure the following:

Field	Value
Database	trino
SQLAlchemy URI	trino://admin:password@coordinator:8443/hive
Impersonate the logged on user	enable it
Secure Extra	{"connect_args": {"verify": false}}
Security	Paste content of ca.crt and trino.crt

Click Test Connection to verify the configuration is ok. Once configured, open http://localhost:9000/superset/sqllab and execute

select * 
from hive.finance.activity
limit 2

The query should return some data.

Log out and try to login as user1 with password "password". Select data from hive.finance.activity.

select *
from hive.finance.activity 
limit 2;

This should result in successful query execution and with some data being displayed. Behind the scenes, trino driver sent impersonation header for user1 even though the connection is established with admin user.

Let's try query that user1 does not have access to run.

select * 
from tpch.sf1.nation
limit 2

The following error should be displayed when running the above query as user1.

Unexpected Error
base error: Access Denied: Cannot select from table tpch.sf1.nation

Impersonation configuration for superset queries is also present in security/rules/rules.json

,
  "impersonation": [
    {
      "original_user": "(admin|dev)",
      "new_user": ".*",
      "allow": true
    },
    {
      "original_user": "skhatri",
      "new_user": "admin",
      "allow": false
    },
    {
      "original_user": "skhatri",
      "new_user": ".*",
      "allow": true
    }
  ]
  }

Query via REST call

Note, you can also run the query via command line like so:

curl --cacert ./certs/trino.crt \
--header "Authorization: Basic YWRtaW46cGFzc3dvcmQ=" \
--header "X-Trino-Source: trino-python-client" \
--header "X-Trino-Time-Zone: UTC" \
--header "User-Agent: trino-cli" \
--header "X-Trino-User: user1" \
--header "X-Trino-Catalog: hive" \
--header "X-Trino-Schema: fitness" \
--data "select * from hive.fitness.activity" \
https://coordinator:8443/v1/statement/

The query runs asynchronously and result is to be collected by the client by calling url returned as nextUri.

{"id":"20220507_202039_00316_z589m","infoUri":"https://coordinator:8443/ui/query.html?20220507_202039_00316_z589m","nextUri":"https://coordinator:8443/v1/statement/queued/20220507_202039_00316_z589m/y66e5ba5e33aa4a2d883eb1de5b1b34a70d49fa5b/1","stats":{"state":"QUEUED","queued":true,"scheduled":false,"nodes":0,"totalSplits":0,"queuedSplits":0,"runningSplits":0,"completedSplits":0,"cpuTimeMillis":0,"wallTimeMillis":0,"queuedTimeMillis":0,"elapsedTimeMillis":0,"processedRows":0,"processedBytes":0,"physicalInputBytes":0,"peakMemoryBytes":0,"spilledBytes":0},"warnings":[]}

curl --cacert ./certs/trino.crt \
--header "Authorization: Basic YWRtaW46cGFzc3dvcmQ=" \
--header "X-Trino-Source: trino-python-client" \
--header "X-Trino-Time-Zone: UTC" \
--header "User-Agent: trino-cli" \
--header "X-Trino-User: user1" \
--header "X-Trino-Catalog: hive" \
--header "X-Trino-Schema: fitness" \
https://coordinator:8443/v1/statement/queued/20220507_202039_00316_z589m/y66e5ba5e33aa4a2d883eb1de5b1b34a70d49fa5b/1

{"id":"20220507_202039_00316_z589m","infoUri":"https://coordinator:8443/ui/query.html?20220507_202039_00316_z589m","nextUri":"https://coordinator:8443/v1/statement/queued/20220507_202039_00316_z589m/y2a208f52803793fff6721c73899be69224a8361b/2","stats":{"state":"QUEUED","queued":true,"scheduled":false,"nodes":0,"totalSplits":0,"queuedSplits":0,"runningSplits":0,"completedSplits":0,"cpuTimeMillis":0,"wallTimeMillis":0,"queuedTimeMillis":3,"elapsedTimeMillis":5,"processedRows":0,"processedBytes":0,"physicalInputBytes":0,"peakMemoryBytes":0,"spilledBytes":0},"warnings":[]}

We will keep on calling nextUri

curl --cacert ./certs/trino.crt \
--header "Authorization: Basic YWRtaW46cGFzc3dvcmQ=" \
--header "X-Trino-Source: trino-python-client" \
--header "X-Trino-Time-Zone: UTC" \
--header "User-Agent: trino-cli" \
--header "X-Trino-User: user1" \
--header "X-Trino-Catalog: hive" \
--header "X-Trino-Schema: fitness" \
https://coordinator:8443/v1/statement/queued/20220507_202039_00316_z589m/y2a208f52803793fff6721c73899be69224a8361b/2

The response is returned but it has access denied exception. This is valid as we are trying to impersonate "user1" who does not have access to hive.fitness.activity

{"id":"20220507_202039_00316_z589m","infoUri":"https://coordinator:8443/ui/query.html?20220507_202039_00316_z589m","stats":{"state":"FAILED","queued":false,"scheduled":false,"nodes":0,"totalSplits":0,"queuedSplits":0,"runningSplits":0,"completedSplits":0,"cpuTimeMillis":0,"wallTimeMillis":0,"queuedTimeMillis":3,"elapsedTimeMillis":46,"processedRows":0,"processedBytes":0,"physicalInputBytes":0,"peakMemoryBytes":0,"spilledBytes":0},"error":{"message":"Access Denied: Cannot select from table hive.fitness.activity","errorCode":4,"errorName":"PERMISSION_DENIED","errorType":"USER_ERROR","failureInfo":{"type":"io.trino.spi.security.AccessDeniedException","message":"Access Denied: Cannot select from table hive.fitness.activity","suppressed":[]}

We will now remove the impersonation user and try the query again.

curl --cacert ./certs/trino.crt \
--header "Authorization: Basic YWRtaW46cGFzc3dvcmQ=" \
--header "X-Trino-Source: trino-python-client" \
--header "X-Trino-Time-Zone: UTC" \
--header "User-Agent: trino-cli" \
--header "X-Trino-Catalog: hive" \
--header "X-Trino-Schema: fitness" \
--data "select * from hive.fitness.activity limit 1" \
https://coordinator:8443/v1/statement/

Clients like superset have the configuration to poll for response. In the background, they would also be calling nextUri just like we are.

{"id":"20220507_204009_00318_z589m","infoUri":"https://coordinator:8443/ui/query.html?20220507_204009_00318_z589m","nextUri":"https://coordinator:8443/v1/statement/queued/20220507_204009_00318_z589m/yd279ea2a17c75c545a33a7e2ca6ef153fbb8959d/1","stats":{"state":"QUEUED","queued":true,"scheduled":false,"nodes":0,"totalSplits":0,"queuedSplits":0,"runningSplits":0,"completedSplits":0,"cpuTimeMillis":0,"wallTimeMillis":0,"queuedTimeMillis":0,"elapsedTimeMillis":0,"processedRows":0,"processedBytes":0,"physicalInputBytes":0,"peakMemoryBytes":0,"spilledBytes":0},"warnings":[]}

call retrieve what is in nextUri

curl --cacert ./certs/trino.crt \
--header "Authorization: Basic YWRtaW46cGFzc3dvcmQ=" \
--header "X-Trino-Source: trino-python-client" \
--header "X-Trino-Time-Zone: UTC" \
--header "User-Agent: trino-cli" \
--header "X-Trino-Catalog: hive" \
--header "X-Trino-Schema: fitness" \
https://coordinator:8443/v1/statement/queued/20220507_204009_00318_z589m/yd279ea2a17c75c545a33a7e2ca6ef153fbb8959d/1

{"id":"20220507_204009_00318_z589m","infoUri":"https://coordinator:8443/ui/query.html?20220507_204009_00318_z589m","nextUri":"https://coordinator:8443/v1/statement/queued/20220507_204009_00318_z589m/ye6a1823d14841fe8b51fe72c8128097f23cbfd2c/2","stats":{"state":"QUEUED","queued":true,"scheduled":false,"nodes":0,"totalSplits":0,"queuedSplits":0,"runningSplits":0,"completedSplits":0,"cpuTimeMillis":0,"wallTimeMillis":0,"queuedTimeMillis":8,"elapsedTimeMillis":9,"processedRows":0,"processedBytes":0,"physicalInputBytes":0,"peakMemoryBytes":0,"spilledBytes":0},"warnings":[]}

Let's keep on calling nextUri for completeness.

curl --cacert ./certs/trino.crt \
--header "Authorization: Basic YWRtaW46cGFzc3dvcmQ=" \
--header "X-Trino-Source: trino-python-client" \
--header "X-Trino-Time-Zone: UTC" \
--header "User-Agent: trino-cli" \
--header "X-Trino-Catalog: hive" \
--header "X-Trino-Schema: fitness" \
https://coordinator:8443/v1/statement/queued/20220507_204009_00318_z589m/ye6a1823d14841fe8b51fe72c8128097f23cbfd2c/2

{"id":"20220507_204009_00318_z589m","infoUri":"https://coordinator:8443/ui/query.html?20220507_204009_00318_z589m","nextUri":"https://coordinator:8443/v1/statement/executing/20220507_204009_00318_z589m/y210ffea7ebcb7b54ef598335bf18e2b331427888/0","stats":{"state":"QUEUED","queued":true,"scheduled":false,"nodes":0,"totalSplits":0,"queuedSplits":0,"runningSplits":0,"completedSplits":0,"cpuTimeMillis":0,"wallTimeMillis":0,"queuedTimeMillis":8,"elapsedTimeMillis":21373,"processedRows":0,"processedBytes":0,"physicalInputBytes":0,"peakMemoryBytes":0,"spilledBytes":0},"warnings":[]}

curl --cacert ./certs/trino.crt \
--header "Authorization: Basic YWRtaW46cGFzc3dvcmQ=" \
--header "X-Trino-Source: trino-python-client" \
--header "X-Trino-Time-Zone: UTC" \
--header "User-Agent: trino-cli" \
--header "X-Trino-Catalog: hive" \
--header "X-Trino-Schema: fitness" \
https://coordinator:8443/v1/statement/executing/20220507_204009_00318_z589m/y210ffea7ebcb7b54ef598335bf18e2b331427888/0

The final response has the columns and data attributes.

{"id":"20220507_204009_00318_z589m","infoUri":"https://coordinator:8443/ui/query.html?20220507_204009_00318_z589m","partialCancelUri":"https://coordinator:8443/v1/statement/executing/partialCancel/20220507_204009_00318_z589m/1/yc1e5c2e839286131959d53aec4c005e10c352b6b/1","nextUri":"https://coordinator:8443/v1/statement/executing/20220507_204009_00318_z589m/yc1e5c2e839286131959d53aec4c005e10c352b6b/1","columns":[{"name":"activity_date","type":"date","typeSignature":{"rawType":"date","arguments":[]}},{"name":"average_weight","type":"varchar","typeSignature":{"rawType":"varchar","arguments":[{"kind":"LONG","value":2147483647}]}},{"name":"max_weight","type":"varchar","typeSignature":{"rawType":"varchar","arguments":[{"kind":"LONG","value":2147483647}]}},{"name":"min_weight","type":"varchar","typeSignature":{"rawType":"varchar","arguments":[{"kind":"LONG","value":2147483647}]}},{"name":"calories","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"heart_points","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"heart_minutes","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"low_latitude","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"low_longitude","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"high_latitude","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"high_longitude","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"step_count","type":"integer","typeSignature":{"rawType":"integer","arguments":[]}},{"name":"distance","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"average_speed","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"max_speed","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"min_speed","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"move_minutes_count","type":"integer","typeSignature":{"rawType":"integer","arguments":[]}},{"name":"cycling_duration","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"inactive_duration","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"walking_duration","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"running_duration","type":"real","typeSignature":{"rawType":"real","arguments":[]}},{"name":"load_date","type":"date","typeSignature":{"rawType":"date","arguments":[]}}],"data":[["2019-10-03","","","",2909.2954,72.0,63.0,33.9449,-122.476845,37.809143,-118.40078,19363,13745.628,1.3299762,18.032257,0.045891136,222,null,6.4861504E7,7164427.0,6170764.0,"2021-03-06"]],"stats":{"state":"RUNNING","queued":false,"scheduled":true,"nodes":2,"totalSplits":7,"queuedSplits":0,"runningSplits":1,"completedSplits":6,"cpuTimeMillis":32,"wallTimeMillis":143,"queuedTimeMillis":8,"elapsedTimeMillis":39369,"processedRows":521,"processedBytes":96423,"physicalInputBytes":96423,"peakMemoryBytes":638,"spilledBytes":0,"rootStage":{"stageId":"0","state":"RUNNING","done":false,"nodes":1,"totalSplits":5,"queuedSplits":0,"runningSplits":0,"completedSplits":5,"cpuTimeMillis":3,"wallTimeMillis":4,"processedRows":1,"processedBytes":574,"physicalInputBytes":0,"failedTasks":0,"coordinatorOnly":false,"subStages":[{"stageId":"1","state":"PENDING","done":false,"nodes":2,"totalSplits":2,"queuedSplits":0,"runningSplits":1,"completedSplits":1,"cpuTimeMillis":29,"wallTimeMillis":139,"processedRows":521,"processedBytes":96423,"physicalInputBytes":96423,"failedTasks":0,"coordinatorOnly":false,"subStages":[]}]},"progressPercentage":85.71428571428571},"warnings":[]}

Running with Envoy

Although trino has its plugin system for observability and acl, it is also possible to put envoy proxy on top of coordinator.

The benefits of this can be

free observability through envoy
possible ACL or additional rules applied enforced in envoy filter
zero-downtime trino upgrades
traffic load shedding based on user, time etc

Optionally, create trino-proxy certificate which can be configured for trino-proxy envoy instance.

./ca.sh trino-proxy

The below script uses trino-proxy to queue up the query and retrieves data by polling the response.

query="select * from hive.fitness.activity limit 1"
user="user2"
next_uri=$(curl -s -o out.json -k --cacert ./certs/trino-proxy/bundle.crt \
--header "Authorization: Basic $(echo -n admin:password|base64)" \
--header "X-Trino-User: ${user}" \
--data "${query}" \
https://trino-proxy:8453/v1/statement/|jq -r '.nextUri')
while true;
do
    curl -s -o out.json -k --cacert ./certs/trino-proxy/bundle.crt \
    --header "Authorization: Basic $(echo -n admin:password|base64)" \
    --header "X-Trino-User: ${user}" \
    ${next_uri}
    cat out.json
    next_uri=$(cat out.json|jq -r '.nextUri')
    if [[ "${next_uri}" == "null" ]];
    then
        break;
    fi;
    sleep 1;
done;

skhatri / trino-by-example Goto Github PK

trino-by-example's Introduction