mirror of
https://gitlab.com/pulsechaincom/erigon-pulse.git
synced 2025-01-06 02:52:19 +00:00
62fe81e4be
* etl.Loader - allow use of custom comparator * log timing * try now * try now * more performance * etl.Loader - allow use of custom comparator * working version * simplify IH cursor * clean * squash * squash * squash * squash * squash * squash * squash * clean * add only unwind support * squash * squash * clean * fix test * clean * clean * clean
92 lines
3.3 KiB
Python
92 lines
3.3 KiB
Python
import csv
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import struct
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import plotly.express as px
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import pandas as pd
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import lmdb
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import sys
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import chain
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import dbutils
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import common
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# apt install python3-snappy libgmp3-dev && pip3 install trinity lmdb pandas plotly
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cmd = sys.argv[1]
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chaindata = sys.argv[2]
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env = lmdb.open(chaindata, max_dbs=100, readonly=True, subdir=True, map_size=32 * 1024 * 1024 * 1024, create=False)
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analyticsEnv = lmdb.open("analytics", max_dbs=100, readonly=False, subdir=True, map_size=32 * 1024 * 1024 * 1024,
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create=True)
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env.reader_check() # clear stale reads
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def allBuckets(env):
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buckets = []
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root = env.open_db(None, create=False)
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with env.begin(write=False) as txn:
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with txn.cursor(root) as curs:
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for i, (k, v) in enumerate(curs.iternext()):
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buckets.append(k.decode("utf-8"))
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return buckets
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if cmd == "stats":
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data = {"name": [], "size": []}
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for bucket in allBuckets(env):
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b = env.open_db(bucket.encode(), create=False)
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with env.begin(write=False) as txn:
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stat = txn.stat(b)
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size = stat['psize'] * (stat['branch_pages'] + stat['leaf_pages'] + stat['overflow_pages'])
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print("%s: %dMb %dM" % (bucket, size/1024/1024, stat['entries']/1000/1000))
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# data["name"].append(bucket)
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# data["size"].append(stat['psize'] * (stat['branch_pages'] + stat['leaf_pages'] + stat['overflow_pages']))
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# df = pd.DataFrame.from_dict(data)
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# fig = px.pie(df, values='size', names='name', title='Buckets size')
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# fig.show()
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elif cmd == "gas_limits":
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StartedWhenBlockNumber = chain.lastBlockNumber(env)
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b = env.open_db(dbutils.HeaderPrefix, create=False)
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mainHashes = analyticsEnv.open_db("gl_main_hashes".encode(), create=True)
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def collect_main_hashes(readTx, writeTx):
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with readTx.cursor(b) as curs:
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for i, (k, v) in enumerate(curs.iternext()):
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timestamp = common.bytesToUint64(k[:common.BlockNumberLength])
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if timestamp > StartedWhenBlockNumber:
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break
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if not dbutils.isHeaderHashKey(k):
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continue
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mainHash = bytes(v)
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writeTx.put(mainHash, common.uint64ToBytes(0), mainHashes)
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def gas_limits(readTx, writeTx, file):
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blockNum = 0
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with readTx.cursor(b) as curs:
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for i, (k, v) in enumerate(curs.iternext()):
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timestamp = common.bytesToUint64(k[:common.BlockNumberLength])
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if timestamp > StartedWhenBlockNumber:
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break
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if not dbutils.isHeaderKey(k):
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continue
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val = writeTx.get(k[common.BlockNumberLength:], None, mainHashes)
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if val is None:
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continue
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header = chain.decode_block_header(v)
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file.writerow([blockNum, header.GasLimit])
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blockNum += 1
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with env.begin(write=False) as txn:
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with analyticsEnv.begin(write=True) as writeTx:
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with open('gas_limits.csv', 'w') as csvfile:
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collect_main_hashes(txn, writeTx)
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print("Preloaded: %d" % writeTx.stat(mainHashes)["entries"])
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gas_limits(txn, writeTx, csv.writer(csvfile))
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else:
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print("unknown command %s" % cmd)
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