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new 5b7fe5328 [Minor] Minor English changes. (#4752)
5b7fe5328 is described below
commit 5b7fe53287686571f081ec29b3d290e4717406d4
Author: Justin Mclean <[email protected]>
AuthorDate: Thu Aug 29 12:35:57 2024 +1000
[Minor] Minor English changes. (#4752)
### What changes were proposed in this pull request?
Minor English changes.
### Why are the changes needed?
Clarify a few words here and there. Use Apache in the first instance.
Fix: # N/A
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Compiled locally.
---
docs/how-to-use-the-playground.md | 40 +++++++++++++++++++--------------------
1 file changed, 19 insertions(+), 21 deletions(-)
diff --git a/docs/how-to-use-the-playground.md
b/docs/how-to-use-the-playground.md
index 294f600c9..c0914c385 100644
--- a/docs/how-to-use-the-playground.md
+++ b/docs/how-to-use-the-playground.md
@@ -7,7 +7,7 @@ license: "This software is licensed under the Apache License
version 2."
## Playground introduction
-The playground is a complete Apache Gravitino Docker runtime environment with
`Hive`, `HDFS`, `Trino`, `MySQL`, `PostgreSQL`, `Jupyter`, and a `Gravitino`
server.
+The playground is a complete Apache Gravitino Docker runtime environment with
`Apache Hive`, `HDFS`, `Trino`, `MySQL`, `PostgreSQL`, `Jupyter`, and a `Apache
Gravitino` server.
Depending on your network and computer, startup time may take 3-5 minutes.
Once the playground environment has started, you can open
[http://localhost:8090](http://localhost:8090) in a browser to access the
Gravitino Web UI.
@@ -17,7 +17,7 @@ Install Git and Docker Compose.
## TCP ports used
-The playground runs a number of services. The TCP ports used may clash with
existing services you run, such as MySQL or Postgres.
+The playground runs several services. The TCP ports used may clash with
existing services you run, such as MySQL or Postgres.
| Docker container | Ports used |
|-----------------------|----------------------|
@@ -30,7 +30,7 @@ The playground runs a number of services. The TCP ports used
may clash with exis
## Start playground
-### Launch all components of playground
+### Launch all components of the playground
```shell
git clone [email protected]:apache/gravitino-playground.git
@@ -38,7 +38,7 @@ cd gravitino-playground
./launch-playground.sh
```
-### Launch special component or components of playground
+### Launching a component of the playground
```shell
git clone [email protected]:apache/gravitino-playground.git
@@ -46,10 +46,9 @@ cd gravitino-playground
./launch-playground.sh hive|gravitino|trino|postgresql|mysql|spark|jupyter
```
-Note. Components have dependencies, only launching one or several components
cannot experience
-the full functionality of the playground.
+Note. Components have dependencies, so not launching all components may
prevent you from experiencing the full functionality of the playground.
-## Experiencing Apache Gravitino with Trino SQL
+## Using Apache Gravitino with Trino SQL
### Using Trino CLI in Docker Container
@@ -109,7 +108,7 @@ SHOW TABLES from catalog_hive.company;
### Cross-catalog queries
-In a company, there may be different departments using different data stacks.
In this example, the HR department uses Apache Hive to store its data and the
sales department uses PostgreSQL. You can run some interesting queries by
joining the two departments' data together with Gravitino.
+In a company, there may be different departments using different data stacks.
In this example, the HR department uses Apache Hive to store its data, and the
sales department uses PostgreSQL. You can run some interesting queries by
joining the two departments' data together with Gravitino.
To know which employee has the largest sales amount, run this SQL:
@@ -148,9 +147,9 @@ GROUP BY e.employee_id, given_name, family_name;
### Using Apache Iceberg REST service
-If you want to migrate your business from Hive to Iceberg. Some tables will
use Hive, and the other tables will use Iceberg.
-Gravitino provides an Iceberg REST catalog service, too. You can use Spark to
access REST catalog to write the table data.
-Then, you can use Trino to read the data from the Hive table joining the
Iceberg table.
+Suppose you want to migrate your business from Hive to Iceberg. Some tables
will use Hive, and the other tables will use Iceberg.
+Gravitino provides an Iceberg REST catalog service. You can use Spark to
access the REST catalog to write the table data.
+Then, you can use Trino to read the data from the Hive table and join it with
the Iceberg table.
`spark-defaults.conf` is as follows (It's already configured in the
playground):
@@ -183,7 +182,7 @@ insert into customers (customer_id, customer_name,
customer_email) values (12,'J
```
2. Login Trino container and execute the steps.
-You can get all the customers from both the Hive and Iceberg table.
+You can get all the customers from both the Hive and Iceberg tables.
```shell
docker exec -it playground-trino bash
@@ -201,21 +200,20 @@ select * from catalog_iceberg.sales.customers;
### Using Gravitino with LlamaIndex
-Gravitino playground also provides a simple RAG demo with LlamaIndex. This
demo will show you the
-ability of using Gravitino to manage both tabular and non-tabular dataset,
connecting to
+The Gravitino playground also provides a simple RAG demo with LlamaIndex. This
demo will show you the
+ability to use Gravitino to manage both tabular and non-tabular datasets,
connecting to
LlamaIndex as a unified data source, then use LlamaIndex and LLM to query both
tabular and
non-tabular data with one natural language query.
-The demo is located in the `jupyter` folder, you can open the
`gravitino_llama_index_demo.ipynb`
+The demo is located in the `jupyter` folder, and you can open the
`gravitino_llama_index_demo.ipynb`
demo via Jupyter Notebook by [http://localhost:18888](http://localhost:18888).
The scenario of this demo is that basic structured city statistics data is
stored in MySQL, and
-detailed city introductions are stored in PDF files. The user wants to know
the answers to the
-cities both in the structured data and the PDF files.
+detailed city introductions are stored in PDF files. The user wants to find
answers about cities in the structured data and the PDF files.
-In this demo, you will use Gravitino to manage the MySQL table using
relational catalog, pdf
-files using fileset catalog, treated Gravitino as a unified data source for
LlamaIndex to build
-indexes on both tabular and non-tabular data. Then you will use LLM to query
the data with natural
+In this demo, you will use Gravitino to manage the MySQL table using a
relational catalog, pdf
+files using a fileset catalog, treating Gravitino as a unified data source for
LlamaIndex to build
+indexes on both tabular and non-tabular data. Then you will use LLM to query
the data using natural
language queries.
Note: to run this demo, you need to set `OPENAI_API_KEY` in the
`gravitino_llama_index_demo.ipynb`,
@@ -228,4 +226,4 @@ os.environ["OPENAI_API_KEY"] = ""
os.environ["OPENAI_API_BASE"] = ""
```
-<img
src="https://analytics.apache.org/matomo.php?idsite=62&rec=1&bots=1&action_name=HowtoUsePlayground";
style={{ border: 0 }} alt="" />
\ No newline at end of file
+<img
src="https://analytics.apache.org/matomo.php?idsite=62&rec=1&bots=1&action_name=HowtoUsePlayground";
style={{ border: 0 }} alt="" />
