Graf Node

Graph Node is the component which indexes Subgraphs, and makes the resulting data available to query via a GraphQL API. As such it is central to the indexer stack, and correct operation of Graph Node is crucial to running a successful indexer.

This provides a contextual overview of Graph Node, and some of the more advanced options available to indexers. Detailed documentation and instructions can be found in the Graph Node repository⁠.

Graf Node

Graph Node⁠ is the reference implementation for indexing Subgraphs on The Graph Network, connecting to blockchain clients, indexing Subgraphs and making indexed data available to query.

Graph Node (and the whole indexer stack) can be run on bare metal, or in a cloud environment. This flexibility of the central indexing component is crucial to the robustness of The Graph Protocol. Similarly, Graph Node can be built from source⁠, or indexers can use one of the provided Docker Images⁠.

PostgreSQL-databas

The main store for the Graph Node, this is where Subgraph data is stored, as well as metadata about Subgraphs, and Subgraph-agnostic network data such as the block cache, and eth_call cache.

Nätverkskunder

För att indexera ett nätverk behöver Graf Node åtkomst till en nätverksklient via ett EVM-kompatibelt JSON-RPC API. Denna RPC kan ansluta till en enda klient eller så kan det vara en mer komplex konfiguration som lastbalanserar över flera.

While some Subgraphs may just require a full node, some may have indexing features which require additional RPC functionality. Specifically Subgraphs which make eth_calls as part of indexing will require an archive node which supports EIP-1898⁠, and Subgraphs with callHandlers, or blockHandlers with a call filter, require trace_filter support (see trace module documentation here⁠).

Network Firehoses - a Firehose is a gRPC service providing an ordered, yet fork-aware, stream of blocks, developed by The Graph’s core developers to better support performant indexing at scale. This is not currently an Indexer requirement, but Indexers are encouraged to familiarise themselves with the technology, ahead of full network support. Learn more about the Firehose here⁠.

IPFS-noder

Subgraph deployment metadata is stored on the IPFS network. The Graph Node primarily accesses the IPFS node during Subgraph deployment to fetch the Subgraph manifest and all linked files. Network indexers do not need to host their own IPFS node. An IPFS node for the network is hosted at https://ipfs.thegraph.com⁠.

Prometheus server för mätvärden

För att möjliggöra övervakning och rapportering kan Graf Node valfritt logga metrik till en Prometheus-metrisk server.

Getting started from source

Install prerequisites

• Rust

• PostgreSQL

• IPFS

• Additional Requirements for Ubuntu users - To run a Graph Node on Ubuntu a few additional packages may be needed.

1sudo apt-get install -y clang libpq-dev libssl-dev pkg-config

Setup

1. Start a PostgreSQL database server

1initdb -D .postgres2pg_ctl -D .postgres -l logfile start3createdb graph-node

2. Clone Graph Node⁠ repo and build the source by running cargo build

3. Now that all the dependencies are setup, start the Graph Node:

1cargo run -p graph-node --release -- \2  --postgres-url postgresql://[USERNAME]:[PASSWORD]@localhost:5432/graph-node \3  --ethereum-rpc [NETWORK_NAME]:[URL] \4  --ipfs https://ipfs.thegraph.com

Komma igång med Kubernetes

A complete Kubernetes example configuration can be found in the indexer repository⁠.

Portar

När Graph Node är igång exponerar den följande portar:

Avancerad konfiguration av Graf Node

At its simplest, Graph Node can be operated with a single instance of Graph Node, a single PostgreSQL database, an IPFS node, and the network clients as required by the Subgraphs to be indexed.

This setup can be scaled horizontally, by adding multiple Graph Nodes, and multiple databases to support those Graph Nodes. Advanced users may want to take advantage of some of the horizontal scaling capabilities of Graph Node, as well as some of the more advanced configuration options, via the config.toml file and Graph Node’s environment variables.

config.toml

A TOML⁠ configuration file can be used to set more complex configurations than those exposed in the CLI. The location of the file is passed with the —config command line switch.

A minimal config.toml file can be provided; the following file is equivalent to using the —postgres-url command line option:

1[store]2[store.primary]3connection="<.. postgres-url argument ..>"4[deployment]5[[deployment.rule]]6indexers = [ "<.. list of all indexing nodes ..>" ]

Full documentation of config.toml can be found in the Graph Node docs⁠.

Flera Grafnoder

Graph Node indexing can scale horizontally, running multiple instances of Graph Node to split indexing and querying across different nodes. This can be done simply by running Graph Nodes configured with a different node_id on startup (e.g. in the Docker Compose file), which can then be used in the config.toml file to specify dedicated query nodes, block ingestors, and splitting Subgraphs across nodes with deployment rules.

Regler för utplacering

Given multiple Graph Nodes, it is necessary to manage deployment of new Subgraphs so that the same Subgraph isn’t being indexed by two different nodes, which would lead to collisions. This can be done by using deployment rules, which can also specify which shard a Subgraph’s data should be stored in, if database sharding is being used. Deployment rules can match on the Subgraph name and the network that the deployment is indexing in order to make a decision.

Exempel på konfiguration av deployeringsregler:

1[deployment]2[[deployment.rule]]3match = { name = "(vip|important)/.*" }4shard = "vip"5indexers = [ "index_node_vip_0", "index_node_vip_1" ]6[[deployment.rule]]7match = { network = "kovan" }8# No shard, so we use the default shard called 'primary'9indexers = [ "index_node_kovan_0" ]10[[deployment.rule]]11match = { network = [ "xdai", "poa-core" ] }12indexers = [ "index_node_other_0" ]13[[deployment.rule]]14# There's no 'match', so any Subgraph matches15shards = [ "sharda", "shardb" ]16indexers = [17    "index_node_community_0",18    "index_node_community_1",19    "index_node_community_2",20    "index_node_community_3",21    "index_node_community_4",22    "index_node_community_5"23  ]

Read more about deployment rules here⁠.

Dedikerade frågenoder

Noder kan konfigureras för att uttryckligen vara frågenoder genom att inkludera följande i konfigurationsfilen:

1[general]2query = "<regular expression>"

Alla noder vars —node-id matchar reguljärt uttryck kommer att konfigureras för att endast svara på förfrågningar.

Skalning av databas via sharding

För de flesta användningsfall är en enda Postgres-databas tillräcklig för att stödja en graph-node-instans. När en graph-node-instans växer utöver en enda Postgres-databas är det möjligt att dela upp lagringen av graph-node-data över flera Postgres-databaser. Alla databaser tillsammans bildar lagringsutrymmet för graph-node-instansen. Varje individuell databas kallas en shard.

Shards can be used to split Subgraph deployments across multiple databases, and can also be used to use replicas to spread query load across databases. This includes configuring the number of available database connections each graph-node should keep in its connection pool for each database, which becomes increasingly important as more Subgraphs are being indexed.

Sharding blir användbart när din befintliga databas inte kan hålla jämna steg med belastningen som Graph Node sätter på den och när det inte längre är möjligt att öka databasens storlek.

När det gäller att konfigurera anslutningar, börja med max_connections i postgresql.conf som är inställt på 400 (eller kanske till och med 200) och titta på Prometheus-metrarna store_connection_wait_time_ms och store_connection_checkout_count. Märkbara väntetider (något över 5 ms) är en indikation på att det finns för få anslutningar tillgängliga; höga väntetider beror också på att databasen är mycket upptagen (som hög CPU-belastning). Om databasen verkar annars stabil, indikerar höga väntetider att antalet anslutningar behöver ökas. I konfigurationen är det en övre gräns för hur många anslutningar varje graph-node-instans kan använda, och Graph Node kommer inte att hålla anslutningar öppna om det inte behöver dem.

Read more about store configuration here⁠.

Intag av dedikerade block

If there are multiple nodes configured, it will be necessary to specify one node which is responsible for ingestion of new blocks, so that all configured index nodes aren’t polling the chain head. This is done as part of the chains namespace, specifying the node_id to be used for block ingestion:

1[chains]2ingestor = "block_ingestor_node"

Stöd för flera nätverk

The Graph Protocol is increasing the number of networks supported for indexing rewards, and there exist many Subgraphs indexing unsupported networks which an indexer would like to process. The config.toml file allows for expressive and flexible configuration of:

• Flera nätverk
• Flera leverantörer per nätverk (detta kan göra det möjligt att dela upp belastningen mellan leverantörer, och kan också möjliggöra konfiguration av fullständiga noder samt arkivnoder, där Graph Node föredrar billigare leverantörer om en viss arbetsbelastning tillåter det).
• Ytterligare information om leverantören, t. ex. funktioner, autentisering och typ av leverantör (för stöd för experimentell Firehose)

The [chains] section controls the ethereum providers that graph-node connects to, and where blocks and other metadata for each chain are stored. The following example configures two chains, mainnet and kovan, where blocks for mainnet are stored in the vip shard and blocks for kovan are stored in the primary shard. The mainnet chain can use two different providers, whereas kovan only has one provider.

1[chains]2ingestor = "block_ingestor_node"3[chains.mainnet]4shard = "vip"5provider = [6  { label = "mainnet1", url = "http://..", features = [], headers = { Authorization = "Bearer foo" } },7  { label = "mainnet2", url = "http://..", features = [ "archive", "traces" ] }8]9[chains.kovan]10shard = "primary"11provider = [ { label = "kovan", url = "http://..", features = [] } ]

Read more about provider configuration here⁠.

Miljö variabler

Graph Node supports a range of environment variables which can enable features, or change Graph Node behaviour. These are documented here⁠.

Kontinuerlig driftsättning

Användare som driver en skalad indexering med avancerad konfiguration kan dra nytta av att hantera sina Graph Nodes med Kubernetes.

• The indexer repository has an example Kubernetes reference⁠
• Launchpad⁠ is a toolkit for running a Graph Protocol Indexer on Kubernetes maintained by GraphOps. It provides a set of Helm charts and a CLI to manage a Graph Node deployment.

Hantera Graf Noder

Given a running Graph Node (or Graph Nodes!), the challenge is then to manage deployed Subgraphs across those nodes. Graph Node surfaces a range of tools to help with managing Subgraphs.

Loggning

Graph Node’s logs can provide useful information for debugging and optimisation of Graph Node and specific Subgraphs. Graph Node supports different log levels via the GRAPH_LOG environment variable, with the following levels: error, warn, info, debug or trace.

In addition setting GRAPH_LOG_QUERY_TIMING to gql provides more details about how GraphQL queries are running (though this will generate a large volume of logs).

Monitoring & alerting

Graph Node tillhandahåller metrikerna via Prometheus-endpunkt på port 8040 som standard. Grafana kan sedan användas för att visualisera dessa metriker.

The indexer repository provides an example Grafana configuration⁠.

Graphman

graphman is a maintenance tool for Graph Node, helping with diagnosis and resolution of different day-to-day and exceptional tasks.

The graphman command is included in the official containers, and you can docker exec into your graph-node container to run it. It requires a config.toml file.

Full documentation of graphman commands is available in the Graph Node repository. See [/docs/graphman.md] (https://github.com/graphprotocol/graph-node/blob/master/docs/graphman.md⁠) in the Graph Node /docs

Working with Subgraphs

Indexerings status API

Available on port 8030/graphql by default, the indexing status API exposes a range of methods for checking indexing status for different Subgraphs, checking proofs of indexing, inspecting Subgraph features and more.

The full schema is available here⁠.

Prestanda för indexering

Det finns tre separata delar av indexeringsprocessen:

• Hämta intressanta händelser från leverantören
• Bearbeta händelser i rätt ordning med lämpliga hanterare (detta kan innebära att kedjan anropas för status och att data hämtas från lagret)
• Skriva de resulterande data till butiken

These stages are pipelined (i.e. they can be executed in parallel), but they are dependent on one another. Where Subgraphs are slow to index, the underlying cause will depend on the specific Subgraph.

Vanliga orsaker till indexeringslångsamhet:

• Time taken to find relevant events from the chain (call handlers in particular can be slow, given the reliance on trace_filter)
• Making large numbers of eth_calls as part of handlers
• En stor mängd butiksinteraktion under exekvering
• En stor mängd data att spara i butiken
• Ett stort antal evenemang att bearbeta
• Långsam databasanslutningstid, för överbelastade noder
• Leverantören själv faller bakom kedjehuvudet
• Långsamhet vid hämtning av nya kvitton från leverantören vid kedjehuvudet

Subgraph indexing metrics can help diagnose the root cause of indexing slowness. In some cases, the problem lies with the Subgraph itself, but in others, improved network providers, reduced database contention and other configuration improvements can markedly improve indexing performance.

Failed Subgraphs

During indexing Subgraphs might fail, if they encounter data that is unexpected, some component not working as expected, or if there is some bug in the event handlers or configuration. There are two general types of failure:

• Deterministiska fel: detta är fel som inte kommer att lösas med retries
• Icke-deterministiska fel: dessa kan bero på problem med leverantören eller något oväntat Graph Node-fel. När ett icke-deterministiskt fel inträffar kommer Graph Node att försöka igen med de felande hanterarna och backa över tid.

In some cases a failure might be resolvable by the indexer (for example if the error is a result of not having the right kind of provider, adding the required provider will allow indexing to continue). However in others, a change in the Subgraph code is required.

Blockera och anropa cache

Graph Node caches certain data in the store in order to save refetching from the provider. Blocks are cached, as are the results of eth_calls (the latter being cached as of a specific block). This caching can dramatically increase indexing speed during “resyncing” of a slightly altered Subgraph.

However, in some instances, if an Ethereum node has provided incorrect data for some period, that can make its way into the cache, leading to incorrect data or failed Subgraphs. In this case indexers can use graphman to clear the poisoned cache, and then rewind the affected Subgraphs, which will then fetch fresh data from the (hopefully) healthy provider.

Om en blockcache-inkonsekvens misstänks, som att en tx-kvitto saknar händelse:

1. graphman chain list to find the chain name.
2. graphman chain check-blocks <CHAIN> by-number <NUMBER> will check if the cached block matches the provider, and deletes the block from the cache if it doesn’t.
   1. If there is a difference, it may be safer to truncate the whole cache with graphman chain truncate <CHAIN>.
   2. Om blocket matchar leverantören kan problemet felsökas direkt mot leverantören.

Fråga frågor och fel

Once a Subgraph has been indexed, indexers can expect to serve queries via the Subgraph’s dedicated query endpoint. If the indexer is hoping to serve significant query volume, a dedicated query node is recommended, and in case of very high query volumes, indexers may want to configure replica shards so that queries don’t impact the indexing process.

Men även med en dedikerad frågenod och repliker kan vissa frågor ta lång tid att utföra, och i vissa fall öka minnesanvändningen och negativt påverka frågetiden för andra användare.

Det finns inte en “silverkula”, men en rad verktyg för att förebygga, diagnostisera och hantera långsamma frågor.

Fråge cachning

Graph Node caches GraphQL queries by default, which can significantly reduce database load. This can be further configured with the GRAPH_QUERY_CACHE_BLOCKS and GRAPH_QUERY_CACHE_MAX_MEM settings - read more here⁠.

Analyserar frågor

Problematic queries most often surface in one of two ways. In some cases, users themselves report that a given query is slow. In that case the challenge is to diagnose the reason for the slowness - whether it is a general issue, or specific to that Subgraph or query. And then of course to resolve it, if possible.

I andra fall kan utlösaren vara hög minnesanvändning på en frågenod, i vilket fall utmaningen först är att identifiera frågan som orsakar problemet.

Indexers can use qlog⁠ to process and summarize Graph Node’s query logs. GRAPH_LOG_QUERY_TIMING can also be enabled to help identify and debug slow queries.

Med en långsam fråga har indexörer några alternativ. Självklart kan de ändra sin kostnadsmodell för att kraftigt öka kostnaden för att skicka den problematiska frågan. Detta kan resultera i att frekvensen av den frågan minskar. Men det löser ofta inte grunden till problemet.

Kontoliknande optimering

Databastabeller som lagrar enheter verkar generellt komma i två varianter: ‘transaktionsliknande’, där enheter, när de väl är skapade, aldrig uppdateras, dvs. de lagrar något liknande en lista över finansiella transaktioner, och ‘konto-liknande’, där enheter uppdateras mycket ofta, dvs. de lagrar något som finansiella konton som ändras varje gång en transaktion registreras. Tabeller med konto-liknande tabeller karakteriseras av att de innehåller ett stort antal enhetsversioner, men relativt få distinkta enheter. Ofta är antalet distinkta enheter i sådana tabeller 1% av det totala antalet rader (enhetsversioner)

For account-like tables, graph-node can generate queries that take advantage of details of how Postgres ends up storing data with such a high rate of change, namely that all of the versions for recent blocks are in a small subsection of the overall storage for such a table.

The command graphman stats show <sgdNNNN> shows, for each entity type/table in a deployment, how many distinct entities, and how many entity versions each table contains. That data is based on Postgres-internal estimates, and is therefore necessarily imprecise, and can be off by an order of magnitude. A -1 in the entities column means that Postgres believes that all rows contain a distinct entity.

In general, tables where the number of distinct entities are less than 1% of the total number of rows/entity versions are good candidates for the account-like optimization. When the output of graphman stats show indicates that a table might benefit from this optimization, running graphman stats show <sgdNNN> <table> will perform a full count of the table - that can be slow, but gives a precise measure of the ratio of distinct entities to overall entity versions.

Once a table has been determined to be account-like, running graphman stats account-like <sgdNNN>.<table> will turn on the account-like optimization for queries against that table. The optimization can be turned off again with graphman stats account-like --clear <sgdNNN>.<table> It takes up to 5 minutes for query nodes to notice that the optimization has been turned on or off. After turning the optimization on, it is necessary to verify that the change does not in fact make queries slower for that table. If you have configured Grafana to monitor Postgres, slow queries would show up in pg_stat_activityin large numbers, taking several seconds. In that case, the optimization needs to be turned off again.

For Uniswap-like Subgraphs, the pair and token tables are prime candidates for this optimization, and can have a dramatic effect on database load.

Removing Subgraphs

At some point an indexer might want to remove a given Subgraph. This can be easily done via graphman drop, which deletes a deployment and all it’s indexed data. The deployment can be specified as either a Subgraph name, an IPFS hash Qm.., or the database namespace sgdNNN. Further documentation is available here⁠.