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Posts Indexer

info

NEAR QueryAPI is currently under development. Users who want to test-drive this solution need to be added to the allowlist before creating or forking QueryAPI indexers.

You can request access through this link or by contacting us in the Near Indexer Builder Group on Telegram.

Overview

This indexer creates a new row in a pre-defined posts table created by the user in the GraphQL database for every new post found on the blockchain. This is a simple example that shows how to specify a single table, filter blockchain transaction data for a specific type of transaction, and save the data to the database.

tip

This indexer can be found by following this link.

Defining the Database Schema

The first step to creating an indexer is to define the database schema. This is done by editing the schema.sql file in the code editor. The schema for this indexer looks like this:

CREATE TABLE
"posts" (
"id" SERIAL NOT NULL,
"account_id" VARCHAR NOT NULL,
"block_height" DECIMAL(58, 0) NOT NULL,
"receipt_id" VARCHAR NOT NULL,
"content" TEXT NOT NULL,
"block_timestamp" DECIMAL(20, 0) NOT NULL,
CONSTRAINT "posts_pkey" PRIMARY KEY ("id")
);

This schema defines a table called posts with columns:

  • id: a unique identifier for each row in the table
  • account_id: the account ID of the user who created the post
  • block_height: the height of the block in which the post was created
  • receipt_id: the receipt ID of the transaction that created the post
  • content: the content of the post
  • block_timestamp: the timestamp of the block in which the post was created

Defining the Indexing Logic

The next step is to define the indexing logic. This is done by editing the indexingLogic.js file in the code editor. The logic for this indexer can be divided into two parts:

  1. Filtering blockchain transactions for a specific type of transaction
  2. Saving the data from the filtered transactions to the database

Filtering Blockchain Transactions

The first part of the logic is to filter blockchain transactions for a specific type of transaction. This is done by using the getBlock function. This function takes in a block and a context and returns a promise. The block is a Near Protocol block, and the context is a set of helper methods to retrieve and commit state. The getBlock function is called for every block on the blockchain.

The getBlock function for this indexer looks like this:

import { Block } from "@near-lake/primitives";

async function getBlock(block: Block, context) {
function base64decode(encodedValue) {
let buff = Buffer.from(encodedValue, "base64");
return JSON.parse(buff.toString("utf-8"));
}

const SOCIAL_DB = "social.near";

const nearSocialPosts = block
.actions()
.filter((action) => action.receiverId === SOCIAL_DB)
.flatMap((action) =>
action.operations
.map((operation) => operation["FunctionCall"])
.filter((operation) => operation?.method_name === "set")
.map((functionCallOperation) => ({
...functionCallOperation,
args: base64decode(functionCallOperation.args),
receiptId: action.receiptId,
}))
.filter((functionCall) => {
const accountId = Object.keys(functionCall.args.data)[0];
return (
Object.keys(functionCall.args.data[accountId]).includes("post") ||
Object.keys(functionCall.args.data[accountId]).includes("index")
);
})
);

... // Further logic for saving nearSocialPosts to the database
}

This function first defines a helper function called base64decode that decodes base64 encoded data. It then defines a constant called SOCIAL_DB that is the name of the database that stores the posts from the BOS. It then filters the blockchain transactions for a specific type of transaction. This is done by:

  1. Filtering the blockchain transactions for transactions where the receiverId is the SOCIAL_DB database
  2. Mapping the operations of the filtered transactions to the FunctionCall operation
  3. Filtering the FunctionCall operations for operations where the method_name is set
  4. Mapping the filtered FunctionCall operations to an object that contains the FunctionCall operation, the decoded args of the FunctionCall operation, and the receiptId of the transaction
  5. Filtering the mapped objects for objects where the args contain a post or index key

This function returns an array of objects that contain the FunctionCall operation, the decoded args of the FunctionCall operation, and the receiptId of the transaction. This array is called nearSocialPosts.

Saving the Data to the Database

The second part of the logic is to save the data from the filtered transactions to the database. This is done by using the context.graphql function. This function takes in a string for the graphQL query and returns a promise. The context.graphql function will be called for every filtered transaction as defined by the .map() function called on the array of nearSocialPosts.

The context.graphql function for this indexer looks like this:

  ... // Logic for filtering blockchain transactions, defining nearSocialPosts

if (nearSocialPosts.length > 0) {
const blockHeight = block.blockHeight;
const blockTimestamp = block.header().timestampNanosec;
await Promise.all(
nearSocialPosts.map(async (postAction) => {
const accountId = Object.keys(postAction.args.data)[0];
console.log(`ACCOUNT_ID: ${accountId}`);

// create a post if indeed a post
if (
postAction.args.data[accountId].post &&
Object.keys(postAction.args.data[accountId].post).includes("main")
) {
try {
console.log("Creating a post...");
const mutationData = {
post: {
account_id: accountId,
block_height: blockHeight,
block_timestamp: blockTimestamp,
receipt_id: postAction.receiptId,
content: postAction.args.data[accountId].post.main,
},
};
await context.graphql(`
mutation CreatePost($post: PostInput!) {
insert_somepublicaddress_near_postsexample_posts_one(
object: $post
) {
account_id
block_height
}
}`,
mutationData
);
console.log(`Post by ${accountId} has been added to the database`);
} catch (e) {
console.error(`Error creating a post by ${accountId}: ${e}`);
}
}
})
);
}

Querying data from the indexer

The final step is querying the indexer using the public GraphQL API. This can be done by writing a GraphQL query using the GraphiQL tab in the code editor.

For example, here's a query that fetches posts from the Posts Indexer, ordered by block_height:

query MyQuery {
<user-name>_near_posts_indexer_posts(order_by: {block_height: desc}) {
content
block_height
account_id
}
}

Once you have defined your query, you can use the GraphiQL Code Exporter to auto-generate a JavaScript or BOS Widget code snippet. The exporter will create a helper method fetchGraphQL which will allow you to fetch data from the indexer's GraphQL API. It takes three parameters:

  • operationsDoc: A string containing the queries you would like to execute.
  • operationName: The specific query you want to run.
  • variables: Any variables to pass in that your query supports, such as offset and limit for pagination.

Next, you can call the fetchGraphQL function with the appropriate parameters and process the results.

Here's the complete code snippet for a BOS component using the Posts Indexer:

const QUERYAPI_ENDPOINT = `https://near-queryapi.api.pagoda.co/v1/graphql/`;

State.init({
data: []
});

const query = `query MyPostsQuery {
<user-name>_near_posts_indexer_posts(order_by: {block_height: desc}) {
content
block_height
account_id
}
}`

function fetchGraphQL(operationsDoc, operationName, variables) {
return asyncFetch(
QUERYAPI_ENDPOINT,
{
method: "POST",
headers: { "x-hasura-role": `<user-name>_near` },
body: JSON.stringify({
query: operationsDoc,
variables: variables,
operationName: operationName,
}),
}
);
}

fetchGraphQL(query, "MyPostsQuery", {}).then((result) => {
if (result.status === 200) {
if (result.body.data) {
const data = result.body.data.<user-name>_near_posts_indexer_posts;
State.update({ data })
console.log(data);
}
}
});

const renderData = (a) => {
return (
<div key={JSON.stringify(a)}>
{JSON.stringify(a)}
</div>
);
};

const renderedData = state.data.map(renderData);
return (
{renderedData}
);
tip

To view a more complex example, see this widget which fetches posts with proper pagination: Posts Widget powered By QueryAPI.