Blob inclusion

Show all code

Analysis of blob inclusion patterns in Ethereum mainnet blocks.

Blobs included per slot¶

Each dot represents a slot, colored by the number of blobs included (0–9). This shows the temporal distribution of blob activity—gaps indicate missed slots or blocks without blobs.

View query

SELECT
    s.slot AS slot,
    s.slot_start_date_time AS time,
    COALESCE(b.blob_count, 0) AS blob_count
FROM (
    SELECT DISTINCT slot, slot_start_date_time
    FROM default.canonical_beacon_block
    WHERE meta_network_name = 'mainnet'
      AND slot_start_date_time >= '2026-05-08' AND slot_start_date_time < '2026-05-08'::date + INTERVAL 1 DAY
) s
LEFT JOIN (
    SELECT
        slot,
        COUNT(*) AS blob_count
    FROM default.canonical_beacon_blob_sidecar
    WHERE meta_network_name = 'mainnet'
      AND slot_start_date_time >= '2026-05-08' AND slot_start_date_time < '2026-05-08'::date + INTERVAL 1 DAY
    GROUP BY slot
) b ON s.slot = b.slot
ORDER BY s.slot ASC

Show code

df_blobs_per_slot = load_parquet("blobs_per_slot", target_date)

fig = px.scatter(
    df_blobs_per_slot,
    x="time",
    y="blob_count",
    color="blob_count",
    color_continuous_scale="YlOrRd",
    labels={"time": "Time", "blob_count": "Blob Count", "slot": "Slot"},
    template="plotly",
    hover_data={"slot": True, "time": True, "blob_count": True},
)
fig.update_traces(
    marker=dict(size=3),
    hovertemplate="<b>Slot:</b> %{customdata[0]}<br><b>Time:</b> %{x}<br><b>Blob Count:</b> %{y}<extra></extra>",
)
fig.update_layout(
    margin=dict(l=60, r=30, t=30, b=60),
    autosize=True,
    showlegend=False,
    yaxis=dict(dtick=1, range=[-0.5, 15.5], title=dict(standoff=10)),
    xaxis=dict(title=dict(standoff=15)),
    coloraxis_colorbar=dict(title=dict(text="Blobs", side="right")),
    height=600,
)
fig.show(config={"responsive": True})