240 lines
6.2 KiB
Markdown
240 lines
6.2 KiB
Markdown
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# Time-Series Database Schema Specification
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## Overview
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This document specifies the time-series database schema using ClickHouse or TimescaleDB for storing mempool data, metrics, and analytics time-series data.
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## Technology Choice
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**Option 1: TimescaleDB** (PostgreSQL extension)
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- Pros: PostgreSQL compatibility, SQL interface, easier integration
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- Cons: Less optimized for very high throughput
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**Option 2: ClickHouse**
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- Pros: Very high performance, columnar storage, excellent compression
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- Cons: Different SQL dialect, separate infrastructure
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**Recommendation**: Start with TimescaleDB for easier integration, migrate to ClickHouse if needed for scale.
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## TimescaleDB Schema
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### Mempool Transactions Table
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**Table**: `mempool_transactions`
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```sql
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CREATE TABLE mempool_transactions (
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time TIMESTAMPTZ NOT NULL,
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chain_id INTEGER NOT NULL,
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hash VARCHAR(66) NOT NULL,
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from_address VARCHAR(42) NOT NULL,
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to_address VARCHAR(42),
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value NUMERIC(78, 0),
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gas_price BIGINT,
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max_fee_per_gas BIGINT,
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max_priority_fee_per_gas BIGINT,
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gas_limit BIGINT,
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nonce BIGINT,
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input_data_length INTEGER,
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first_seen TIMESTAMPTZ NOT NULL,
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status VARCHAR(20) DEFAULT 'pending', -- 'pending', 'confirmed', 'dropped'
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confirmed_block_number BIGINT,
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confirmed_at TIMESTAMPTZ,
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PRIMARY KEY (time, chain_id, hash)
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);
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SELECT create_hypertable('mempool_transactions', 'time');
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CREATE INDEX idx_mempool_chain_hash ON mempool_transactions(chain_id, hash);
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CREATE INDEX idx_mempool_chain_from ON mempool_transactions(chain_id, from_address);
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CREATE INDEX idx_mempool_chain_status ON mempool_transactions(chain_id, status, time);
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```
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**Retention Policy**: 7 days for detailed data, aggregates for longer periods
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### Network Metrics Table
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**Table**: `network_metrics`
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```sql
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CREATE TABLE network_metrics (
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time TIMESTAMPTZ NOT NULL,
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chain_id INTEGER NOT NULL,
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block_number BIGINT,
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tps DOUBLE PRECISION, -- Transactions per second
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gps DOUBLE PRECISION, -- Gas per second
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avg_gas_price BIGINT,
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pending_transactions INTEGER,
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block_time_seconds DOUBLE PRECISION,
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PRIMARY KEY (time, chain_id)
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);
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SELECT create_hypertable('network_metrics', 'time');
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CREATE INDEX idx_network_metrics_chain_time ON network_metrics(chain_id, time DESC);
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```
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**Aggregation**: Pre-aggregate to 1-minute, 5-minute, 1-hour intervals
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### Gas Price History Table
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**Table**: `gas_price_history`
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```sql
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CREATE TABLE gas_price_history (
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time TIMESTAMPTZ NOT NULL,
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chain_id INTEGER NOT NULL,
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block_number BIGINT,
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min_gas_price BIGINT,
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max_gas_price BIGINT,
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avg_gas_price BIGINT,
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p25_gas_price BIGINT, -- 25th percentile
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p50_gas_price BIGINT, -- 50th percentile (median)
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p75_gas_price BIGINT, -- 75th percentile
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p95_gas_price BIGINT, -- 95th percentile
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p99_gas_price BIGINT, -- 99th percentile
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PRIMARY KEY (time, chain_id)
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);
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SELECT create_hypertable('gas_price_history', 'time');
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```
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### Address Activity Metrics Table
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**Table**: `address_activity_metrics`
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```sql
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CREATE TABLE address_activity_metrics (
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time TIMESTAMPTZ NOT NULL,
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chain_id INTEGER NOT NULL,
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address VARCHAR(42) NOT NULL,
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transaction_count INTEGER,
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received_count INTEGER,
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sent_count INTEGER,
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total_received NUMERIC(78, 0),
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total_sent NUMERIC(78, 0),
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PRIMARY KEY (time, chain_id, address)
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);
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SELECT create_hypertable('address_activity_metrics', 'time',
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chunk_time_interval => INTERVAL '1 day');
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CREATE INDEX idx_address_activity_chain_address ON address_activity_metrics(chain_id, address, time DESC);
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```
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**Aggregation**: Pre-aggregate to hourly/daily for addresses
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## ClickHouse Schema (Alternative)
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### Mempool Transactions Table
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```sql
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CREATE TABLE mempool_transactions (
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time DateTime('UTC') NOT NULL,
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chain_id UInt32 NOT NULL,
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hash String NOT NULL,
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from_address String NOT NULL,
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to_address Nullable(String),
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value Decimal128(0),
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gas_price UInt64,
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max_fee_per_gas Nullable(UInt64),
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max_priority_fee_per_gas Nullable(UInt64),
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gas_limit UInt64,
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nonce UInt64,
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input_data_length UInt32,
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first_seen DateTime('UTC') NOT NULL,
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status String DEFAULT 'pending',
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confirmed_block_number Nullable(UInt64),
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confirmed_at Nullable(DateTime('UTC'))
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) ENGINE = MergeTree()
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PARTITION BY toYYYYMM(time)
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ORDER BY (chain_id, time, hash)
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TTL time + INTERVAL 7 DAY; -- Auto-delete after 7 days
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```
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## Data Retention and Aggregation
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### Retention Policies
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**Raw Data**:
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- Mempool transactions: 7 days
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- Network metrics: 30 days
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- Gas price history: 90 days
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- Address activity: 30 days
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**Aggregated Data**:
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- 1-minute aggregates: 90 days
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- 5-minute aggregates: 1 year
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- 1-hour aggregates: 5 years
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- Daily aggregates: Indefinite
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### Continuous Aggregates (TimescaleDB)
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```sql
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-- 1-minute network metrics aggregate
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CREATE MATERIALIZED VIEW network_metrics_1m
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WITH (timescaledb.continuous) AS
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SELECT
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time_bucket('1 minute', time) AS bucket,
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chain_id,
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AVG(tps) AS avg_tps,
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AVG(gps) AS avg_gps,
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AVG(avg_gas_price) AS avg_gas_price,
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AVG(pending_transactions) AS avg_pending_tx
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FROM network_metrics
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GROUP BY bucket, chain_id;
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-- Add refresh policy
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SELECT add_continuous_aggregate_policy('network_metrics_1m',
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start_offset => INTERVAL '1 hour',
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end_offset => INTERVAL '1 minute',
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schedule_interval => INTERVAL '1 minute');
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```
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## Query Patterns
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### Recent Mempool Transactions
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```sql
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SELECT * FROM mempool_transactions
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WHERE chain_id = 138
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AND time > NOW() - INTERVAL '1 hour'
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AND status = 'pending'
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ORDER BY time DESC
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LIMIT 100;
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```
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### Gas Price Statistics
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```sql
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SELECT
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time_bucket('5 minutes', time) AS bucket,
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AVG(avg_gas_price) AS avg_gas_price,
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PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY avg_gas_price) AS median_gas_price
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FROM gas_price_history
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WHERE chain_id = 138
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AND time > NOW() - INTERVAL '24 hours'
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GROUP BY bucket
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ORDER BY bucket DESC;
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```
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### Network Throughput
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```sql
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SELECT
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time_bucket('1 minute', time) AS bucket,
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AVG(tps) AS avg_tps,
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MAX(tps) AS max_tps
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FROM network_metrics
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WHERE chain_id = 138
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AND time > NOW() - INTERVAL '1 hour'
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GROUP BY bucket
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ORDER BY bucket DESC;
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```
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## References
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- Mempool Service: See `../mempool/mempool-service.md`
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- Observability: See `../observability/metrics-monitoring.md`
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