exp/services/ledgerexporter: Add guide for contributors/developers (#…

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Co-authored-by: shawn <[email protected]>
Co-authored-by: George <[email protected]>

exp/services/ledgerexporter/DEVELOPER_GUIDE.md

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+# Ledger Exporter Developer Guide
+The ledger exporter is a tool to export Stellar network transaction data to cloud storage in a way that is easy to access.
+
+## Prerequisites
+This document assumes that you have installed and can run the ledger exporter, and that you have familiarity with its CLI and configuration. If not, please refer to the [Installation Guide](./README.md).
+
+## Goal
+The goal of the ledger exporter is to build an easy-to-use tool to export Stellar network ledger data to a configurable remote data store, such as cloud blob storage.
+ - Use cloud storage optimally
+ - Minimize network usage to export
+ - Make it easy and fast to search for a specific ledger or ledger range
+
+## Architecture
+To achieve its goals, the ledger exporter uses the following architecture, which consists of the 3 main components:
+- Captive-core to extract raw transaction metadata from the Stellar Network.
+- Export manager to bundles and organizes the ledgers to get them ready for export.
+- The cloud storage plugin writes to the cloud storage. This is specific to the type of cloud storage, GCS in this case.
+
+
+![ledgerexporter-architecture](./architecture.png)
+
+
+## Data Format
+- Ledger exporter uses a compact and efficient data format called [XDR](https://developers.stellar.org/docs/learn/encyclopedia/data-format/xdr) (External Data Representation), which is a compact binary format. A Stellar Captive Core instance emits data in this format and the data structure is referred to as `LedgerCloseMeta`. The exporter bundles multiple `LedgerCloseMeta`'s into a single object using a custom XDR structure called `LedgerCloseMetaBatch` which is defined in [Stellar-exporter.x](https://github.com/stellar/go/blob/master/xdr/Stellar-exporter.x).
+
+- The metadata for the same batch is also stored alongside each exported object. Supported metadata is defined in [metadata.go](https://github.com/stellar/go/blob/master/support/datastore/metadata.go). 
+
+- Objects are compressed before uploading using the [zstd](http://facebook.github.io/zstd/) (zstandard) compression algorithm to optimize network usage and storage needs.
+
+## Data Storage
+- An example implementation of `DataStore` for GCS, Google Cloud Storage. This plugin is located in the [support](https://github.com/stellar/go/tree/master/support/datastore) package. 
+- The ledger exporter currently implements the interface only for Google Cloud Storage (GCS). The [GCS plugin](https://github.com/stellar/go/blob/master/support/datastore/gcs_datastore.go) uses GCS-specific behaviors like conditional puts, automatic retry, metadata, and CRC checksum.
+
+## Build, Run and Test using Docker
+The Dockerfile contains all the necessary dependencies (e.g., Stellar-core) required to run the ledger exporter. 
+
+- Build: To build the Docker container, use the provided [Makefile](./Makefile). Simply run make `make docker-build` to build a new container after making any changes.
+
+- Run: For instructions on running the Docker container, refer to the [Installation Guide](./README.md).
+
+- Test: To test the Docker container, refer to the [docker-test](./Makefile) command for an example of how to use the [GCS emulator](https://github.com/fsouza/fake-gcs-server) for local testing.
+
+## Adding support for a new storage type
+Support for different data storage types are encapsulated as 'plugins', which are implementation of `DataStore` interface in a go package. To add a data storage plugin based on a new storage type (e.g. AWS S3), follow these steps:
+
+- A data storage plugin must implement the [DataStore](https://github.com/stellar/go/blob/master/support/datastore/datastore.go) interface.
+- Add support for new datastore-specific features. Implement any datastore-specific custom logic. Different datastores have different ways of handling 
+  - race conditions
+  - automatic retries
+  - metadata storage, etc.
+- Add the new datastore to the factory function [NewDataStore](https://github.com/stellar/go/blob/master/support/datastore/datastore.go).
+- Add a [config](./config.example.toml) section for the new storage type. This may include configurations like destination, authentication information etc.
+- An emulator such as a GCS emulator [fake-gcs-server](https://github.com/fsouza/fake-gcs-server) can be used for testing without connecting to real cloud storage.
+
+### Design DOs and DONTs
+- Multiple exporters should be able to run in parallel without the need for explicit locking or synchronization.
+- Exporters when restarted do not have any memory of prior operation and rely on the already exported data as much as possible to decide where to resume.
+
+## Using exported data
+The exported data in storage can be used in the ETL pipeline to gather analytics and reporting. To write a tool that consumes exported data you can use Stellar ingestion library's `ledgerbackend` package. This package includes a ledger backend called [BufferedStorageBackend](https://github.com/stellar/go/blob/master/ingest/ledgerbackend/buffered_storage_backend.go),
+which imports data from the storage and validates it. For more details, refer to the ledgerbackend [documentation](https://github.com/stellar/go/tree/master/ingest/ledgerbackend).
+
+## Contributing
+For information on how to contribute, please refer to our [Contribution Guidelines](https://github.com/stellar/go/blob/master/CONTRIBUTING.md).